# The Jean Nicolas Database. The French Rebellion, 1661-1789

Victor Gay

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## To cite this version:

Victor Gay. The Jean Nicolas Database. The French Rebellion, 1661-1789. Data & Corpus, 2025, 1 (16582), pp.1-55. 10.46298/dc.15892. hal-05117002v4

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# The Jean Nicolas Database

## *The French Rebellion, 1661–1789*

GAY, Victor * ID 1

### Domaines

### Sciences sociales — Histoire

**Date de soumission** : 18 juin 2025

**Date d'acceptation** : 7 novembre 2025

**Date de publication** : 11 décembre 2025

<footnote n="1">¹ Department of Social and Behavioral Sciences, Toulouse School of Economics, University of Toulouse Capitole</footnote>

<footnote>* Mail : victor.gay@tse-fr.eu</footnote>
Résumé

Cet article présente la base de données Jean Nicolas, une ressource exhaustive recensant environ 8 516 rébellions survenues en France entre 1661 et 1789. Fondée sur une enquête menée par Jean Nicolas du début des années 1980 à la fin des années 1990, la base de données consigne pour chaque événement sa typologie, sa chronologie, son lieu, les caractéristiques des participants, les formes de confrontation et de violence, les conséquences judiciaires, les sources et l'auteur de la notice. En plus de détailler la méthodologie de construction de la base, l'article en évalue de manière critique la fiabilité, en analysant les biais introduits lors de la collecte initiale des données. Il fournit également des conseils méthodologiques aux utilisateurs finaux afin d'en atténuer les limites.

Abstract

This article introduces the Jean Nicolas database, a comprehensive resource documenting 8,516 rebellions in France between 1661 and 1789. Based on a survey conducted by Jean Nicolas from the early 1980s to the late 1990s, the database records each event's typology, chronology, location, participant characteristics, forms of confrontation and violence, legal consequences, sources, and authorship. In addition to detailing the construction methodology of the database, the article critically evaluates its reliability by analyzing biases introduced during the original data collection process. It also provides methodological guidance to end users to mitigate the database's limitations.

Mots-clés

conflit social, troubles publics, histoire sociale, histoire européenne, données

Keywords

social conflict, civil disturbances, social history, European history, data

Informations sur le jeu de données

<table><tr><td>Title</td><td>The Jean Nicolas Database</td></tr><tr><td>Author</td><td>Gay, Victor</td></tr><tr><td>Publication date</td><td>2025-09-22 (Version 2.0)<br/>2025-06-17 (Version 1.0)</td></tr><tr><td>Version</td><td>2.0</td></tr></table>
<table><tr><td>Link</td><td>https://doi.org/10.7910/DVN/ANQXMQ</td></tr><tr><td>Identifier</td><td>doi:10.7910/DVN/ANQXMQ</td></tr><tr><td>Availability</td><td>Open access</td></tr><tr><td>License</td><td>CC-BY 4.0</td></tr><tr><td>Formats and metrics</td><td>Database: 6 folders and 9,019 files (2.03 GB)<ul><li>README file (TXT | 5 KB)</li><li>Image file nicolas_logbook (PDF | 22 MB)</li><li>Folder nicolas_records: 8,977 image files (PDF | 1.51 GB)</li><li>Folder nicolas_events: 8 data files (CSV, TXT, DTA | 223 MB)</li><li>Folder nicolas_events_all: 8 data files (CSV, TXT, DTA | 234 MB)</li><li>Folder nicolas.sources: 8 data files (CSV, TXT, DTA | 32 MB)</li><li>Folder nicolas_authors: 8 data files (CSV, TXT, DTA | 123 KB)</li><li>Folder nicolas_hisco: 8 data files (CSV, TXT, DTA | 20 MB)</li></ul></td></tr><tr><td>Language</td><td>en, fr</td></tr><tr><td>Bibliographic reference</td><td>Gay, Victor. (2025, 22 septembre). The Jean Nicolas Database (version 2.0) [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/ANQXMQ</td></tr></table>
# 1. INTRODUCTION

Rebellions have long been a central concern for social scientists and historians. Far from being mere disruptions, episodes of social conflict expose deeper tensions over power, inequality, values, and competing visions of society. Because of their transformative potential, scholars have examined how these conflicts shape a wide range of societal outcomes such as state formation (Slater, 2010), political consciousness (Porchnev, 1963; Thompson, 1971), regime durability (Levitsky & Way, 2013), or collective identity (Le Roy Ladurie, 1966). Early works in this tradition focus on early modern Europe—a period of rapid social and economic change accompanied by the consolidation of state power (Le Roy Ladurie, 1966; Porchnev, 1963; Thompson, 1971; Tilly, 1986). Among these conflicts, the French Revolution stands out as a landmark event that has inspired a vast scholarly literature (e.g., Andress, 2013). Yet the thousands of localized uprisings that erupted across the French countryside throughout the eighteenth century have received comparatively less attention, despite their significance as precursors to the Revolution (Aubert, 2015, 2023; Nicolas, 2002).

In recent years, however, renewed interest in historical political economy and improved access to historical data have spurred a new wave of empirical research on rebellion over this period (Cirone, 2023; Jenkins & Rubin, 2024). A key driver of this resurgence has been the availability of the Historical Social Conflict Database (HiSCoD; Chambru and Maneuvrier-Hervieu, 2024), which compiles about 21 thousand episodes of social conflict in Europe from the High Middle Ages to the late nineteenth century. This resource has proved instrumental in enabling new empirical studies on the roots of rebellion, particularly in early modern France (e.g., Chambru, 2019; Davoine et al., 2025; Degrave, 2023; Giommoni et al., 2025; Jha & Wilkinson, 2023; Ottinger & Rosenberger, 2023). A significant part of the HiSCoD database draws from the Jean Nicolas survey, which documents more than 8,500 rebellious events that occurred in France between 1661 and 1789 (Nicolas 1973, 1974, 1985a, 2002).<fnref n="1" /> However, the database includes only a limited subset of the information originally recorded in the Jean Nicolas survey.<fnref n="2" /> Moreover, the companion article to the database offers little detail about the context in which the Jean Nicolas survey was developed or on the potential biases embedded in its content (Chambru & Maneuvrier-Hervieu, 2024). Yet the meaningful reuse of data from past

<footnote n="1">¹ These events represent about 40 percent of the HiSCoD database and 54 percent of its entries concerning France.</footnote>

<footnote n="2">² The HiSCoD database provides information on the typology, date, location, number and gender of participants of each event, together with the sources and authors of each record.</footnote>
surveys requires a clear understanding of the conditions under which the
data were initially produced (Girault, 2019).

To address these two limitations, I offer a detailed account of the
development of the Jean Nicolas survey, tracing its origins in the early
1970s through to the publication of Jean Nicolas's (2002) seminal book,
*The French Rebellion (La rébellion française)*. In particular, I highlight the
*de facto* regional stratification of the survey. I further examine Jean
Nicolas's definition of the concept of *rebellion*, emphasizing how its broad
scope may blur the line between political unrest and more ambiguous
phenomena, such as ordinary criminal acts (Section 2). I then introduce the
Jean Nicolas database, a comprehensive resource that captures all the
information originally recorded in the Jean Nicolas survey. For each event,
the database documents its typology, chronology, location, participant
characteristics, forms of confrontation and violence, and legal
consequences—a total of 284 variables. In addition, the Jean Nicolas
database includes auxiliary datasets offering detailed information about the
sources and authors of each record. It also provides the scanned images of
all the original records of the Jean Nicolas survey (Section 3). Next, I
provide a critical assessment of the reliability of the Jean Nicolas database.
Specifically, I first compare the content of the database with the
corresponding records in HiSCoD, identifying some discrepancies in
Chambru and Maneuvrier-Hervieu's (2024) database. I then analyze
*quantitatively* the biases introduced by the survey methodology due to
source selection, authorship patterns, and regional archival coverage. I also
propose a grading system that documents the quality of each record
(Section 4). On the basis of this quantitative source criticism exercise, I
offer practical recommendations for researchers using the database in
empirical work to help ensure that their analyses yield robust and credible
results (Section 5). Finally, Section 6 describes the availability of the Jean
Nicolas database, and Section 7, its potential uses.

The construction of the Jean Nicolas database is part of a threefold
movement. First, it reflects the recent revival of quantitative history in both
the French and Anglo-American traditions (Cirone, 2023; Karila-Cohen et
al., 2018; Lemercier & Zalc, 2019; Ruggles, 2021). Second, it contributes to
an ongoing cross-disciplinary movement to upcycle historical data
collections, whose objective is to make these collections interoperable and
reusable through reproducible workflows (Scheltjens, 2023). Finally, it
adopts an interdisciplinary perspective and aims to foster a dialogue
between history and the quantitative social sciences by providing users with
the conceptual tools needed to avoid common pitfalls in quantitative
historical research (Armatte, 2020; Dennison & Gehlbach, 2024; Karila-
Cohen et al., 2018; Lemercier et al., 2013; Lemercier & Zalc, 2019).
## 2. THE JEAN NICOLAS SURVEY OF REBELLIONS

This section traces the development of the Jean Nicolas survey, from its origins in the early 1970s to its eventual digitization in the form of the Jean Nicolas database in 2025 (Section 2.1). It also examines Jean Nicolas's definition of the concept of *rebellion*, which formed the basis for the survey's data collection (Section 2.2).<fnref n="3" />

### 2.1. The Making of the Jean Nicolas Survey

#### 2.1.1. Origins of the Survey (1973–74)

The Jean Nicolas survey of rebellions originated as the initiative of a single historian. While studying the nobility and bourgeoisie of eighteenth-century Savoy (Nicolas, 1978), Jean Nicolas became increasingly interested in the dynamics of popular uprisings. Challenging the prevailing view in the 1970s that popular revolts had largely disappeared by the mid-seventeenth century, he argued that social conflict remained a vital force in shaping historical change well into the eighteenth century. Guided by his Marxist convictions, he sought to restore a sense of “conflictual and creative coherence” to popular action, emphasizing that the people acted rationally and that their participation in conflict had meaningful political implications. This line of inquiry resulted in the programmatic article “Chronicle of Refusal. Toward an Inquiry into Popular Emotions in the Eighteenth Century, the Case of Savoy” (“Éphémérides du refus. Pour une enquête sur les émotions populaires au XVIIIᵉ siècle, le cas de la Savoie”), in which Jean Nicolas compiled 234 rebellions that occurred in Savoy between 1650 and 1792 (Nicolas, 1973, 1974). Although regional in scope—reflecting the broader orientation of French historiography on early modern revolts in the 1970s (Bercé, 1974; Foisil, 1970; Pillorget, 1975)—this study laid the conceptual foundations for what would evolve into a nationwide investigation of popular uprisings.

#### 2.1.2. Design and Launch of the Survey (1982–85)

While Jean Nicolas was the driving force behind the survey from the outset, its concrete design took shape through a collaborative process in 1982–83 as he consulted a number of early modern historians—including Yves-Marie Bercé, Denis Richet, and Hugues Neveux—to define the project’s scope and methodology. The survey aimed to systematically and cumulatively document all traces of popular uprisings in France between the beginning of Louis XIV’s personal reign in 1661 and the outbreak of the French Revolution in 1789. Each event was to be recorded on an individual record through an elaborate coding grid and categorized within a detailed typology. The

<footnote n="3">³ This section draws extensively on Hamon (2021, 2022) as well as informal conversations with Philippe Hamon, who interviewed Jean Nicolas in 2017.</footnote>
resulting (paper-based) database was then to be processed by computer for
statistical analysis.<fnref n="4" />

Following this preparatory phase, the survey was officially launched in
1983. Based in Paris, Jean Nicolas reached out to modern history
professors across France, inviting them to participate directly in the project
or to involve their graduate students.<fnref n="5" /> To achieve comprehensive national
coverage, he tried to articulate three spatial frameworks: the provincial
geography of Ancien Régime France, the spatial distribution of university
centers, and the location of départemental archives—the most promising
archival repositories. This approach resulted in a *de facto* regional
stratification of the survey—Section 4.2 examines the biases introduced by
this strategy. A key moment in the survey’s development came in May 1984
with the conference “Popular Movements and Social Consciousness”
(“Mouvements populaires et conscience sociale”) organized by Jean
Nicolas at Paris–VII. While its thematic scope extended from the fifteenth to
the nineteenth century and beyond France, the event included a dedicated
workshop on the survey. The proceedings of the conference featured the
survey’s typology of protest movements and coding grid (Nicolas, 1985b,
pp. 761–767).<fnref n="6" />

From that point on, Jean Nicolas assumed a central role as both
coordinator and data processor. He personally managed the entire
 workflow: mailing out survey forms, collecting completed records,
numbering them, correcting inconsistencies, and supplementing missing
information when necessary. As uneven regional participation revealed
gaps in the survey's coverage, Jean Nicolas increasingly stepped in as an
investigator, conducting archival research himself to fill these gaps.
Although the data collection was initially scheduled to conclude in 1985, it
ultimately continued until 1999.

2.1.3. Results of the Survey (1986-2002)

The first results of the survey were presented by Jean Nicolas during a
roundtable held at Paris–VII in October 1986 on “Popular Uprisings in
France in the Seventeenth and Eighteenth Centuries.” His unpublished
presentation, titled “Emotions in the Computer. Preliminary Results of a

<footnote n="4">⁴ On the transformative impact of computer-assisted database construction on historical research, see Genet (1986), and more recently, Dedieu (2024).</footnote>

<footnote n="5">⁵ The survey operated with minimal funding. Jean Nicolas occasionally secured financial support from the mission of the Bicentennial of the Revolution and from the 1983 CNRS program "Genesis of the Modern State" ("Genèse de l'État moderne," Genet, 1997). However, the project generally lacked institutional support and relied largely on the unpaid contributions of university faculty.</footnote>

<footnote n="6">⁶ Appendix Figures A1–A3 reproduce the original typology of the survey, while Appendix Figures A4–A7 reproduce its original coding grid.</footnote>
Collective Survey" ("Les émotions dans l'ordinateur. Premiers résultats d'une enquête collective," cited in Markoff, 1990, p. 413), reported 2,878 recorded rebellions. By 1988, the number of documented events had grown to 5,125 (Burguière, 1991).<fnref n="7" /> Although Jean Nicolas retired in 1994, he continued to develop the survey until 1999. In its final version, the survey comprised 8,516 distinct rebellion records. The culmination of this vast undertaking was the publication of Nicolas's (2002) seminal book, *The French Rebellion. Popular Movements and Social Consciousness (1661–1789) (La rébellion française. Mouvements populaires et conscience sociale (1661–1789))*, which extensively drew on his survey.

### 2.1.4.From the Survey to the Database (2015–25)

The original records of the Jean Nicolas survey resurfaced a few years after the publication of *The French Rebellion* thanks to the serendipitous workings of academic networks. Shortly after retiring, Nicolas sought to deposit the forty boxes of survey materials at his home institution, the University of Paris-VII, but the administration declined—as did several other Parisian universities. In 2015, Nicolas raised the issue with Jean Aubert, a historian who had worked in several museums in Savoie, Nicolas’s native region. Jean Aubert then relayed the matter to his son, Gauthier Aubert, who had recently completed his *mémoire* for the Habilitation to Supervise Research on early modern rebellions in Brittany (Aubert, 2014). Seizing the opportunity, Gauthier Aubert personally transported the boxes to his home institution, the University of Rennes-2, where he deposited them at the François Lebrun Library.

In 2017, I contacted Philippe Hamon and Gauthier Aubert to inquire about the whereabouts of Jean Nicolas’s original survey records. I then traveled to the François Lebrun Library, where I digitized the entire collection using a portable scanner.<fnref n="8" /> The 8,977 PDF files of the Jean Nicolas survey—totaling 33,490 pages—are included in the Jean Nicolas database under the *nicolas_records* folder.<fnref n="9" /> Over the following years, and with the assistance of three research assistants, I transcribed the full content of

<footnote n="7">⁷ Appendix Figure A8 reproduces Burguière's (1991) figure of rebellions from 1750 to 1789 drawn based on the Jean Nicolas survey as of 1988.</footnote>

<footnote n="8">⁸ This digitization effort was partially carried out by Estefania Santacreu-Vasut. The resulting scans were distributed in 2021 via the En colère platform (https://www.projetcolere.org/), developed by Pascal Bastien (Université du Québec à Montréal) and Jamie Folsom (Performant Software).</footnote>

<footnote n="9">⁹ This total page count does not correspond to 35,944 (= 8,986 × 4) because some records include supplementary description pages, while others contain two grids per page. Jean Nicolas's logbook tracking his correspondence with collaborators was also deposited at the François Lebrun library and scanned (*nicolas_logbook.pdf*).</footnote>
these records into a Microsoft Access database, which I then processed
and formatted into tabular datasets using the Stata software.<fnref n="10" />

## 2.2. The Notion of Rebellion in the Jean Nicolas Survey

### 2.2.1. The Semantics of Revolt

Before Nicolas's (2002) book, the term *rebellion* was rarely used in the French historiography to describe popular uprisings in early modern France. For instance, in his seminal *History of the Croquants. A Study of Popular Uprisings in 17th-Century Southwestern France* (*Histoire des Croquants. Étude des soulèvements populaires au XVIIᵉ siècle dans le Sud-Ouest de la France*), Bercé (1974, p. 173) uses *rebellions* in a narrow sense, referring specifically to acts led by royal officers. He explicitly distinguishes them from *revolts*, noting that *rebellions* refer to "violent but isolated acts with no lasting consequences." This reflects an implicit hierarchy of intensity by which Bercé (1974) considered *rebellions* as less important than *revolts*.<fnref n="11" />

This preference for an alternative terminology is consistent across the seminal historiography: Porchnev (1963) refers to *popular uprisings*; Mousnier (1967) and Foisil (1970), to *revolts*; and Pillorget (1975), to *insurrectionary movements*. Likewise in historical dictionaries: Cabourdin and Viard's (1978) entries are *peasant revolts* and *emotions*; Pillorget and Pillorget's (1996), *popular uprisings*; and Bély's (1996), *riots and revolts*.

Even Jean Nicolas initially employed alternative terminology. His pioneering 1973–74 article referred to *popular emotions*; the 1984 conference, to *popular movements*; and the 1986 roundtable, to *popular uprisings*, with Jean Nicolas's own presentation referring to *emotions*. It was ultimately with Nicolas's (2002) *The French Rebellion* that the term *rebellion* gained significant visibility, for instance by quickly making its way into Grenier et al.'s (2003) and Bourquin et al.'s (2005) historical dictionaries.

### 2.2.2. What Counts as Rebellion?

In the first chapter of his book, “The Archives of Disorder,” Nicolas (2002, pp. 19–25) revisits the concept of rebellion that guided the construction of his survey. While he draws on categories used by historical actors—such as *emotions*, *riots*, or *sedition*, as found in archival sources—he ultimately constructs his own analytical framework. He defines a rebellion as an event

<footnote n="10">¹⁰ The research assistants who contributed to the transcription were Loris Cuenot, Annie Dago, and Louis Vitrand. This process was supervised in collaboration with Michael Albertus.</footnote>

<footnote n="11">¹¹ Bercé (1974, p. 681) reinforces this distinction in his conclusion, where he describes the topographical unit of *rebellions* as the local community, further suggesting that he associates the term with smaller-scale, localized events.</footnote>
that involves violence, engages at least four individuals from more than one family, may last for only a few hours, and expresses a group's need for survival or collective assertion—his ambition was to “reach the threshold of the barely perceptible, where the most rudimentary forms of awareness emerge” (p. 27).<fnref n="12" /> Although most of these events implicitly involve a confrontation with authorities, this criterion is notably absent from Nicolas's formal definition. In fact, he explicitly includes “violent forms of collective release, neighborhood or parish rivalries, student riots, [and] festive disturbances” (p. 27), which often unfold among social equals and do not necessarily involve any confrontation with authorities. In the specific case of strikes, he even sets aside violence as a necessary criterion (Nicolas, 2002, Footnote 41, p. 27).

Taken together, these criteria allow the Jean Nicolas survey to cast a wide net, capturing the “sporadic” forms of social contestation that might otherwise escape the historian’s scope (Nicolas, 1973, p. 594). However, this expansive scope also presents analytical challenges, as it blurs the boundaries between political unrest and more ambiguous phenomena, such as ordinary criminal acts (e.g., prison escapes) or certain forms of intercommunal violence. As a result, users of the Jean Nicolas database should proceed with caution and pay close attention to the typology of events they include in their analyses.

## 3. THE JEAN NICOLAS DATABASE

The Jean Nicolas database comprises three main datasets: an events dataset (Section 3.1), a sources dataset (Section 3.2), and an authors dataset (Section 3.3).

### 3.1. The Events Dataset

The events dataset (*nicolas_events*) is the central component of the Jean Nicolas database. It provides detailed information on 8,516 distinct rebellions, organized across ten sets of variables. For each rebellion, the dataset records its typology, chronology, location, participant characteristics, forms of confrontation and violence, legal consequences, sources, authorship, and a description of the event—the 284 variables included in the events dataset are listed in Panel A of Appendix Table A1. Each event is assigned a unique four-digit *nicolas* identifier, ranging from

<footnote n="12">¹² Jean Nicolas selected a threshold of four individuals to reflect contemporary regulations that prohibited gatherings exceeding that number when public order was perceived to be under threat (Nicolas, 1985b, p. 75).</footnote>
0001 to 8843 and matching the number found on the top-right corner of each original record.<fnref n="13" />

**Records not included in the events dataset.** The Jean Nicolas survey originally comprises 8,977 records, of which 461 are not included in the final events dataset. These excluded records fall into three categories: deleted, duplicate, and incomplete records. First, Jean Nicolas marked 19 records for deletion, either because they occurred before 1661, did not describe a rebellious event, or were inaccurate.<fnref n="14" /> Second, he identified 238 records as duplicates, typically when multiple authors created distinct records describing the same event—I refer to these as “formal” duplicate records.<fnref n="15" /> In addition, I identified 202 further “effective” duplicates by systematically searching for events that occurred concurrently in the same location and manually inspecting them.<fnref n="16" /> Altogether, the events dataset includes 381 records for which duplicates exist in the original survey. Finally, I removed 2 incomplete records that had not been filled out using the original survey grid.<fnref n="17" /> I provide access to the entire set of records of the Jean Nicolas survey in the *nicolas_events_all* dataset, which includes the same variables as the *nicolas_events* dataset. In addition, this dataset links each duplicate record to the identifier of its corresponding reference record.

### 3.1.1. Typology

The first set of variables concerns the typology of rebellions. Originally developed to encompass 68 types grouped into 13 distinct categories (Nicolas, 1985a, pp. 15–16, 761–763), the typology was later extended to 72 types (Nicolas, 2002, pp. 26–27, 548–550).<fnref n="18" /> Each event is

<footnote n="13">¹³ Each record is also associated with a unique hiscod identifier. See Section 4.1 for more details. Some rebellions are further linked to related events—up to three—by a note on the top-right corner of their original record—this is the case for 315 rebellion records.</footnote>

<footnote n="14">¹⁴ See, e.g., Appendix Figure A9 for an example based on record 1048.</footnote>

<footnote n="15">¹⁵ See, e.g., Appendix Figure A10 for an example based on record 0412.</footnote>

<footnote n="16">¹⁶ In selecting which record to retain as the reference, I prioritized the one kept in the HiSCoD database. Note that reference records were not complemented with the content of their duplicate records, as they may draw from different—and potentially conflicting—sources.</footnote>

<footnote n="17">¹⁷ See, e.g., Appendix Figure A11 for an example based on record 8780. See Appendix Table A2 for the distribution of these types of records.</footnote>

<footnote n="18">¹⁸ Specifically, the types *Opposition to the actions of officers of the Eaux et Forêts jurisdiction (0312)* and *Hiring dispute (1108)* were added to the typology, while the type *Strike (1106)* was subdivided into three types: *Industrial sector strike (1106)*, *Agricultural sector strike (1106)*, and *Agricultural sector strike (1106)*.</footnote>
characterized by a primary general type and primary detailed type. In addition, 24 percent of events are further characterized by a secondary general type and a secondary detailed type. The general typology of rebellions is reported in Table 1.<fnref n="19" /> The most common type of rebellion is *Resistance to state taxation*, which accounts for 37 percent of events, followed by *Resistance to the state judiciary, military, or police* (18 percent), and *Subsistence* (17 percent).

<table><caption>Table 1 – General typology of rebellions.</caption><thead><tr><th rowspan="2">Type of rebellion</th><th colspan="2">Primary</th><th colspan="3">Secondary</th></tr><tr><th>Freq.</th><th>Percent</th><th>Freq.</th><th>Percent</th><th>Valid</th></tr></thead><tbody><tr><td>01 Rejection of state reform initiatives</td><td>52</td><td>0.61</td><td>3</td><td>0.04</td><td>0.15</td></tr><tr><td>02 Resistance to state taxation or incidental taxation</td><td>3,122</td><td>36.66</td><td>320</td><td>3.76</td><td>15.52</td></tr><tr><td>03 Resistance to the state judiciary, military, or police</td><td>1,497</td><td>17.58</td><td>796</td><td>9.35</td><td>38.60</td></tr><tr><td>04 Acts of hostility toward a seigneurial authority</td><td>428</td><td>5.03</td><td>113</td><td>1.33</td><td>5.48</td></tr><tr><td>05 Acts of hostility toward nobility or nobiliary privilege</td><td>13</td><td>0.15</td><td>12</td><td>0.14</td><td>0.58</td></tr><tr><td>06 Acts of hostility toward the Church</td><td>103</td><td>1.21</td><td>159</td><td>1.87</td><td>7.71</td></tr><tr><td>07 Accusation of a notable</td><td>157</td><td>1.84</td><td>70</td><td>0.82</td><td>3.39</td></tr><tr><td>08 Accusation of a municipal authority</td><td>148</td><td>1.74</td><td>111</td><td>1.30</td><td>5.38</td></tr><tr><td>09 Subsistence</td><td>1,483</td><td>17.41</td><td>186</td><td>2.18</td><td>9.02</td></tr><tr><td>010 Religion, beliefs</td><td>265</td><td>3.11</td><td>34</td><td>0.40</td><td>1.65</td></tr><tr><td>011 Labor dispute</td><td>434</td><td>5.10</td><td>61</td><td>0.72</td><td>2.96</td></tr><tr><td>012 Regional idiosyncrasy</td><td>92</td><td>1.08</td><td>46</td><td>0.54</td><td>2.23</td></tr><tr><td>013 Miscellaneous</td><td>722</td><td>8.48</td><td>151</td><td>1.77</td><td>7.32</td></tr><tr><td>Total</td><td>8,516</td><td>100.00</td><td>2,062</td><td>24.21</td><td>100.00</td></tr><tr><td>.c Type missing</td><td>0</td><td>0.00</td><td>6,454</td><td>75.79</td><td></td></tr><tr><td>Total</td><td>8,516</td><td>100.00</td><td>8,516</td><td>100.00</td><td></td></tr></tbody></table>

Notes. This table reports the distribution of the general primary and secondary types of rebellions in the *nicolas_events* dataset. It corresponds to the *typePrim* and *type_sec* variables.

### 3.1.2. Chronology

**Date.** The second set of variables concerns the chronology of rebellions, beginning with the date of each event. Dates are disaggregated into year, month, calendar day, and weekday variables. While the year of each rebellion is systematically available, complete dates are missing in 17 percent of cases.<fnref n="20" /> Figure 1 displays the temporal distribution of recorded rebellions from 1661 to 1789.<fnref n="21" /> It reveals a relatively calm period

<footnote>strike (1109), and Commercial sector strike (1110). The translation of the typology from French to English was carried out by Nicole Charley.</footnote>

<footnote n="19">¹⁹ The detailed typology is reported in Appendix Table A3.</footnote>

<footnote n="20">²⁰ See Appendix Table A4 for the distribution of date variables.</footnote>

<footnote n="21">²¹ Although the Jean Nicolas survey focuses on rebellions that occurred *before* the French Revolution—which began with the opening of the Estates General on May</footnote>
following the upheavals of the 1620s–40s, from the *Cascaveù* in Provence
(Pillorget, 1975) to the *Croquants* in Quercy (Bercé, 1974) and the *Nu-
Pieds* in Normandy (Foisil, 1970). Nevertheless, a few spikes emerge in the
mid-1670s, with the revolt of the Roure in Vivarais in 1670 (Ribon, 2001)
and the revolts of the *Papier Timbré* in Brittany and Guyenne in 1675
(Aubert, 2014), followed by tumults due to the great famine of 1693–94.
Other notable events include the “peasant rage” of the *Tard-Avisés* in
Quercy in 1707 (Gossare, 1997) and the revolutionary outbreak of 1709,
fueled by a subsistence crisis, the War of the Spanish Succession, and
renewed Protestant opposition in the Massif Central (Aubert, 2023). From
the 1730s onward, rebellious activity rises steadily, accelerating sharply
during the 1760s and exceeding one hundred annual events following the
Flour War of 1775 (Bouton, 1993), persisting through the end of the period
and the run-up to the French Revolution.

<figure><img src="image_3.png" /><figcaption>Figure 1 – Temporal Distribution of Rebellions.</figcaption></figure>

Notes. This figure displays the temporal distribution of the 8,516 rebellions in the events dataset based on the *date_year* variable.

An examination of the monthly and daily distribution of rebellions indicates
that neither the month of January nor the first day of the month is
overrepresented, suggesting that recorded dates are reliable.<fnref n="22" />

<footnote>5, 1789—two recorded events occurred *during* the Revolution on May 15 and June 14, 1789.</footnote>

<footnote n="22">²² See Appendix Figure A12. In 262 cases, records specify a date interval, indicating that the event spanned multiple days. For these events, the date variables record both the start and end dates of the rebellion. An additional variable</footnote>
**Period of the Day.** The starting hour of the rebellion is available for 11 percent of events.<fnref n="23" /> However, a broad period of the day—morning (6–12), afternoon (12–18), evening (18–22), and/or night (22–6)—is recorded for 48 percent of them.<fnref n="24" />

In addition, information on the overall duration of the rebellion is available for 52 percent of cases across 5 categories: one hour, one to two hours, half a day, one day, or more than a day. Among the events for which duration information is available, 55 percent lasted less than two hours, suggesting that the Jean Nicolas database captures brief rebellious outbursts with notable precision.<fnref n="25" />

### 3.1.3. Location

The third set of variables concerns the location of rebellions. It is organized into three subsets of variables: an Ancien Régime geography subset, which further includes population information, a contemporary geography subset, and a subset of miscellaneous spatial variables.

**Ancien Régime geography.** I manually match the location of each rebellion to a spatial reference system of 1789 parishes based on the *Histoire Administrative des Communes* (HAC) database. This database—which also serves as a reference framework for the TRF-GIS (Gay, 2021) and COMMUNE (Litvine et al., 2023) databases—is distributed via the website *cassini.ehess* (LaDéHiS, 2021; Motte & Vouloir, 2007) and is (partially) accessible in tabular format (Cristofoli et al., 2021). It contains individual entries for the forty thousand Ancien Régime parishes that appear on Cassini's *Carte générale de la France*—surveyed between 1756 and 1789 (Pelletier, 1990)—and that became municipalities in 1790, then communes in 1793 (see, e.g., Gorry, 2008).

Using the HAC database, I assign a location identifier (cassini) to each rebellion.<fnref n="26" /> 96 percent of rebellions can be assigned to a specific parish

further measures the duration of the rebellion in days. Conditional on lasting more than a single day, these events had an average duration of three days.

<footnote n="23">²³ See Appendix Table A5 for the distribution of hour variables. In 59 cases, an hour interval is recorded. For these events, the hour variable is duplicated to indicate the start and end hour of the rebellion. An additional variable further records the duration of the rebellion in hours. Conditional on an interval being indicated, these rebellions lasted an average of two hours. In 13 cases, the recorded hour contradicts the indicated period of the day. In such instances, I prioritize the period of the day.</footnote>

<footnote n="24">²⁴ See Appendix Table A6 for the distribution of the period of the day variables.</footnote>

<footnote n="25">²⁵ See Appendix Table A7 for the distribution of the duration variable.</footnote>

<footnote n="26">²⁶ Eight rebellions occurred in the modern territories of Switzerland and Belgium and therefore fall outside of the coverage of the HAC database, which is limited to</footnote>
without ambiguity. For 31 cases, however, the original records do not provide a precise location. In such instances, I assign the rebellion to the *chef-lieu* of the relevant canton, *subdélégation*, or province cited in the original record.²⁷ An additional 267 rebellions cannot be precisely located because their records refer to *lieux-dits* or hamlets that did not become municipalities or communes, and are thus absent from the HAC database. In these cases, I assign the rebellion to the relevant village, town, or city mentioned alongside the *lieu-dit* or hamlet.²⁸ Finally, for 54 rebellions, the records refer to locations created after 1789. In these cases, I identify and assign the corresponding parent parish that existed in 1789.²⁹ A flag variable documents each of these ambiguous cases.³⁰

Notwithstanding the considerations discussed above, each rebellion is precisely situated in Ancien Régime geography through its *cassini* identifier and associated spatial coordinates.³¹ The 8,508 rebellions included in the events dataset with a *cassini* identifier span 4,264 distinct parishes (Figure 2). Three cities—Paris, Nantes, Bordeaux—each hosted

the territory of France as of 1999. These cases include rebellions that occurred in the Republic of Geneva (Collonge-Bellerive, Compesières, Corsier, Meinier, and Vésenaz) and in Mariembourg, which was incorporated into the Kingdom of the Netherlands under the Second Treaty of Paris in 1815, and into the Kingdom of Belgium following the Belgian Revolution of 1830.

²⁷ For instance, rebellion 5754 is recorded as having occurred in the canton of Toulouse without further precision. Accordingly, I assign this event to the chef-lieu of the canton, i.e., the parish of Toulouse (37818). See Appendix Figure A13. 9 uncertain cases further involved subjective choices—these are documented in Appendix Table A8.

²⁸ For instance, rebellion 0174 is recorded as having occurred in the hamlet of Les Fontêtes ([Fonteste]) near the village of Saint-Ours. I therefore assign it to the parish of Saint-Ours (33885). See Appendix Figures A14 and A15.

²⁹ For instance, rebellion 0177 is recorded as having occurred in La Sauvetat (35591), a commune established in 1872. I therefore assign it to its parent parish, i.e., Authezat (01964).

³⁰ See Appendix Table A9 for the distribution of this flag variable. Another ambiguity arises when rebellions are reported to have occurred in multiple locations: in seven cases, across multiple parishes (see, e.g., Appendix Figure A16), and in six cases, across an entire region, such as a *bailliage*, an *élection*, or a *généralité* (see, e.g., Appendix Figure A17). In the case of multiple parishes, I assign the most populous one. In the case of a regional rebellion, I assign the *chef-lieu* of the corresponding region. A flag variable documents these cases (see Appendix Table A10).

³¹ The spatial coordinates for parish locations are provided in both RGF93 and WGS84 projections. These coordinates are derived from the *position_1999* variable in Cristofoli et al. (2021)—which is itself based on IGN’s BD-TOPO 1999—supplemented by the *position_cassini* variable for locations that were not communes in 1999.
over 100 events during the period, while 18 locations saw more than 20.<fnref n="32" />
However, the distribution of locations that ever hosted a rebellion is heavily
left-skewed, as the median location hosted only a single event.<fnref n="33" />

<figure><img src="image_4.png" /><figcaption>Figure 2 – Spatial Distribution of Rebellions.</figcaption></figure>

Notes. This figure displays the spatial distribution of the 8,508 rebellions in the *nicolas_events* dataset that have a cassini identifier in RGF93 projection. It is based on the *lat_cassini_rgf* and *lon_cassini_rgf* variables. The underlying shapefile of the Kingdom of France as of 1789 is based on Gay et al.'s (2023) jurisdictions shapefile (Gay et al., 2024). The underlying shapefile of France as of 2021 is based on IGN's (2021) ADMIN-EXPRESS shapefile.

<footnote n="32">³² See Appendix Table A11 for the distribution of the most frequent locations.</footnote>

<footnote n="33">³³ See Appendix Figure A18.</footnote>
Each location is further characterized by a set of historical toponyms: the name of the parish as it appears on Cassini's map, the name of the corresponding municipality as listed on the "Year III copy" of the 1793 population census, and the name of the corresponding commune as listed on the 1801 *Arrêtés de réduction des justices de paix*, which constitute the first official nomenclature of administrative constituencies.<fnref n="34" />

To characterize the nature of rebellion locations within the broader landscape, I include a variable indicating their representation on Cassini's map: as a church tower (parish), a hamlet, a town, a city, an abbey, or a castle.<fnref n="35" /> According to this measure, 43 percent of rebellions occurred in parishes, 10 percent in towns, and 45 percent in cities.<fnref n="36" />

I also include information on the administrative setting of each location as of 1789 based on Brette's (1904) historical atlas and Gay et al.'s (2024) corresponding dataset: its sovereignty, *généralité*, and *bailliage*. 97 percent of rebellion locations were situated within the Kingdom of France, with the remainder largely located in the Duchy of Savoy.<fnref n="37" />

**1793 and 1800 Population.** To further characterize the type of locations that experienced rebellions, I include population information. I draw on the 1793 census for the corresponding municipality and on the 1800 census for the corresponding commune.<fnref n="38" /> Note that population information for 1793 is available for 98 percent of rebellion locations, leaving about 200 cases without population data. There are three primary reasons for these gaps. The first is related to the operations of the 1793 census (Aberdam, 2004; Meuriot, 1918). This census recorded populations at the level of municipalities, which sometimes encompassed multiple parishes that would later be divided into independent communes. As a result, some parishes

<footnote n="34">³⁴ While parish names from Cassini's map and commune names from the 1801 *Arrêtés* are provided by the *nom cassini* and the *nom_1801* variables in Cristofoli et al. (2021), 1793 municipality names are only accessible through the web version of the HAC database. The source of the *nom_an3* variable in Cristofoli et al. (2021) remains unclear.</footnote>

<footnote n="35">³⁵ This classification is derived from the graphie variable in Cristofoli et al. (2021). Appendix Figure A19 illustrates the corresponding map symbols.</footnote>

<footnote n="36">³⁶ See Appendix Table A12 for the distribution of this representation variable.</footnote>

<footnote n="37">³⁷ See Appendix Table A13. I further include information on each location's *intendance* and *subdélégation* as of 1789 as well as *district* and *département* as of 1793 based on Cristofoli et al.'s (2021) dataset. This information is included as it appears in this dataset.</footnote>

<footnote n="38">³⁸ These values are based on the *pop_an3_info*, *pop_an3_val*, *pop_an8_info*, and *pop_an8_val* variables in Cristofoli et al. (2021).</footnote>
did not have distinct population counts.<fnref n="39" /> Moreover, some municipalities were omitted from the census due to the disruptions caused by external wars and civil unrest during its operations. In some cases, original census returns were never recovered.<fnref n="40" /> Finally, Corsica was not included in the 1793 census. Second, some parishes had been absorbed into neighboring ones that became municipalities between 1789 and 1793, and thus were not counted separately in 1793.<fnref n="41" /> Third, a number of parishes were only incorporated into France after 1793.<fnref n="42" /> For these ca. 200 cases, I assign the corresponding population from the 1800 census. Each of these cases is documented with a flag variable. A similar flag variable tracks the ca. 50 missing population values for the 1800 census.<fnref n="43" />

Figure 3 displays the distribution of rebellions across location by 1793 population size. Rebellions were relatively evenly distributed among small, medium, and large municipalities, with a moderate concentration in urban municipalities with more than 5,000 inhabitants.<fnref n="44" /> The median municipality that ever hosted a rebellion had approximately 1,700 inhabitants.<fnref n="45" />

**Contemporary geography.** I also match each parish to its corresponding commune in 2021 geography based on INSEE's (2021) Official geographic code (COG) and IGN's (2021) ADMIN-EXPRESS, so that each location is associated with both an *insee* and an *ign* identifier.<fnref n="46" /> I further include each commune's toponymy, spatial coordinates, and administrative setting—region, *département*, *arrondissement*, and *canton*. Because France's communal landscape consolidated over time (Bideau & Verdier,

<footnote n="39">³⁹ For instance, rebellion 0230 occurred in the parish of Saint-Cirgues (30943), which was grouped in with the parish of La Voutte (19040) in the municipality of La Voutte et Saint Cirgues during the 1793 census.</footnote>

<footnote n="40">⁴⁰ This concerned the municipalities of five districts: La Roche-sur-Yon and Montaigu in the département of Vendée, La Rochefoucauld in the département of Charente, Machecoul in the département of Loire-Inférieure, Sarrelouis in the département of Moselle, and Valenciennes in the département of Nord.</footnote>

<footnote n="41">⁴¹ For instance, rebellion 0397 occurred in the parish of Parilly (61165), which had been absorbed by Chinon (9378) prior to the 1793 census.</footnote>

<footnote n="42">⁴² For instance, rebellion 0397 took place in Mulhouse (24395), which was reunited with France in 1798.</footnote>

<footnote n="43">⁴³ See Appendix Tables A14 and A15 for the distribution of these flag variables.</footnote>

<footnote n="44">⁴⁴ Appendix Figure A20 shows the corresponding distribution using 1800 population figures.</footnote>

<footnote n="45">⁴⁵ See Appendix Table A43 for summary statistics of quantitative variables.</footnote>

<footnote n="46">⁴⁶ The correspondence between *cassini* and *insee* identifiers is based on the *commune_mars_2021* variable in Cristofoli et al. (2021).</footnote>
2024), rebellions are distributed across fewer locations in contemporary than in Ancien Régime geography: 4,149 communes compared to 4,264 parishes.

<figure><img src="image_5.png" /><figcaption>Figure 3 – Distribution of Rebellions by 1793-Municipality Population.</figcaption></figure>

*Notes.* This figure displays the distribution of rebellions by 1793-municipality population for the 8,508 rebellions in the *nicolas_events* dataset that have a *cassini* identifier. It is based on the *pop_1793* variable.

**Miscellaneous spatial variables.** Besides their locations, original rebellion records further contain three spatial indicators: whether the location where the rebellion occurred was higher than 500 meters in altitude, closer than 30 kilometers from a border, and whether there was a strong Protestant presence in the area. I report the original altitude measure alongside the minimum, maximum, and *chef-lieu* altitude of the rebellion location based on contemporary geography.<fnref n="47" /> I also report the original border-distance variable, along with a measure of the distance to the nearest sea or

<footnote n="47">⁴⁷ See Appendix Tables A16 and A43. I match each 2021 commune in the data with France's Digital elevation model (MNT) provided by Sauvion (2024). The original altitude variable is relatively accurate as 99 percent of rebellions recorded as having occurred below 500 meters in the original record are confirmed by the MNT data, while 84 percent of those recorded above 500 meters are likewise confirmed (see Appendix Table A17).</footnote>
external land frontier, and the type of that frontier.<fnref n="48" /> Finally, I report the
original Protestant-presence variable.<fnref n="49" />

3.1.4. Participant Characteristics

The fourth set of variables relates to the characteristics of rebellion
participants. The events dataset records the number of participants in each
event, a broad measure of its “intensity,” and the gender, age, and social
categories of those involved. However, since this information is not
available for all records, users of the Jean Nicolas database should assess
the spatial and temporal representativeness of their sample when including
these variables in their analysis—the same caution applies to the variables
discussed in the following subsections.

**Number of participants.** The number of participants in a rebellion is recorded in various ways, depending on the level of detail provided by source materials: a precise number, an interval, a lower bound, or a relatively vague term. Still, information on rebellion size is entirely missing in 56 percent of cases. To make this information usable in empirical analyses when available, I apply the following transformations: when a participant count is provided as an interval (3 percent of cases), I use the midpoint of this interval; when a lower bound is provided (2 percent), I use this lower bound; and when an approximate number is provided (1 percent), I use the reported figure as-is. I document the nature of the original string provided through a flag variable.<fnref n="50" /> I also retain the original string from rebellion records. For the 3,769 rebellions for which this information is available, the average number of participants is 164, and the median is 21. This distribution is heavily left-skewed.<fnref n="51" /> The Jean Nicolas database thus captures both small and large rebellious events.

**Intensity.** The intensity of a rebellion is an element written by Jean Nicolas in the lower left corner of the first page of each record. It is available for nearly all records (99.5 percent). Ranging from 1 to 3, it indicates the broad importance of the rebellion. As defined in his book (Nicolas, 2002, pp. 27–28), “weak” rebellions (*intensity* = 1) are those with fewer than

<footnote n="48">⁴⁸ See Appendix Tables A18 and A43. These distance measures are calculated based on Gay et al.’s (2023) shapefile of the Kingdom of France as of 1789 (Gay et al., 2024).</footnote>

<footnote n="49">⁴⁹ See Appendix Table A19 for the distribution of the Protestant-presence variable. Users wishing to validate this measure may consult Mours (1958) or Robert (1961).</footnote>

<footnote n="50">⁵⁰ See Appendix Table A20 for the distribution of this flag variable. When the information provided is a vague term (31 cases), such as “foule,” I input the number of participants based on the intensity variable: 7 participants for weak rebellions, 30 for moderate ones, and 100 for strong ones. See below for more details.</footnote>

<footnote n="51">⁵¹ See Appendix Figure A21 for the distribution of the number of participants.</footnote>
10 individuals, “moderate” rebellions (intensity = 2), those with 10–50 individuals, and “strong” rebellions (intensity = 3), those with more than 50 individuals.<fnref n="52" /> However, as discussed above, information on the number of participants is missing in more than half of cases. Jean Nicolas was well aware of this issue.<fnref n="53" /> His solution was to also rely on qualitative information available in the sources.<fnref n="54" /> Per his assessment, 31 percent of rebellions had a weak intensity, 45 percent, a moderate intensity, and 24 percent, a strong intensity.<fnref n="55" />

How accurate is Jean Nicolas’s assessment of the intensity of a rebellion?
While we cannot assess his accuracy for all rebellions, it is possible to do
so for the subset for which we have precise information on the number of
participants, i.e., 38 percent of cases. Appendix Table A22 provides a
tabulation of the intensity measure by participant count bin. Although the
overlap between Jean Nicolas’s assessment and the actual number of
participants is not perfect, it is reasonably accurate as 84 percent of cases
are “correctly” classified ((792 + 979 + 958)/3,254).

**Gender and age composition.** Rebellion records document the gender
composition of rebellion participants in 76 percent of cases, across
8 categories: men and women; only men; mixed, majority men; only
women; mixed, majority women; women and children; men, women, and
children; and only children.<fnref n="56" /> From these measures, I further create an

<footnote n="52">⁵² “Nous avons affecté chaque cas d’un coefficient d’intensité relative en distinguant trois échelons: affaires de faible, de moyenne et de considérable importance, de 4 à 10 participants, de 11 à 50 et plus de 50” (“We have assigned a relative intensity coefficient to each case, distinguishing three levels: small, medium and large cases, from 4 to 10 participants, from 11 to 50 and above 50,” Nicolas, 2002, p. 27).</footnote>

<footnote n="53">⁵³ “On sait que les sources restent souvent imprécises ou peu fiables pour les données chiffrées [sur les participants]” (“One knows that sources are often imprecise or unreliable when it comes to statistics [on participants],” Nicolas, 2002, p. 28).</footnote>

<footnote n="54">⁵⁴ “Nous avons donc tenu compte de toutes les estimations qualitatives fournies par les autorités ou par des témoins” (“We have therefore taken into account all qualitative estimates provided by the authorities or by witnesses,” Nicolas, 2002, p. 28).</footnote>

<footnote n="55">⁵⁵ See Appendix Table A21 for the distribution of the intensity variable. In the 21 cases for which the intensity variable is missing from the original record but information on the number of participants is available, I input the intensity based on this participant count.</footnote>

<footnote n="56">⁵⁶ See Appendix Table A23 for the distribution of the participants variable.</footnote>
indicator variable for whether women participated in the rebellion.<fnref n="57" /> This
was the case for about half of the rebellions for which the gender
composition of participants is documented.

Rebellion records also document the age composition of participants in 94 percent of cases, distinguishing between adults and children. 95 percent of rebellions had a majority of adults.<fnref n="58" />

**Social categories.** The social categories of rioters are documented in 70 percent of cases, across 17 categories: farmers, market gardeners, winemakers, agricultural workers, lumberjacks, artisans, journeymen, industrial workers, domestic servants, soldiers, mariners, inmates, beggars, bohemians, migrants, outcasts, and notables.<fnref n="59" /> Because a rebellion can involve rioters from multiple social categories, I create an indicator variable for each category that takes the value of 1 if that category is mentioned in the rebellion record. The most frequently mentioned social categories are farmers (28 percent of cases), notables (18 percent), artisans (13 percent), and outcasts (12 percent).<fnref n="60" />

**Involvement of notables alongside rioters.** The involvement of notables alongside rioters is documented in 22 percent of cases, across 9 categories of notables: lords, nobles, civil officers or magistrates, lawyers or clerks, priests or members of a religious order, municipal representatives, wealthy commoners, tavern keepers, occult figures, and other categories.<fnref n="61" /> Because different types of notables can be involved alongside rioters, I create an indicator variable for each category that takes the value of 1 if that category is mentioned in the rebellion record. The most frequently mentioned categories of notables are municipal representatives (4 percent

<footnote n="57">⁵⁷ Specifically, this indicator variable takes the value of 1 if the gender composition of the rebellion is men and women; mixed, majority men; only women; mixed, majority women; women and children; or men, women, and children. Conversely, it takes the value of 0 if the gender composition of the rebellion is only men or only children. It takes a missing value if the gender composition of the rebellion is missing. See Appendix Table A24 for the distribution of the gender variable.</footnote>

<footnote n="58">⁵⁸ See Appendix Table A25 for the distribution of the age variable.</footnote>

<footnote n="59">⁵⁹ The original terminology of social categories is *paysans, maraîchers, vignerons, ouvriers agricoles, bûcherons, artisans, compagnons, ouvriers industriels, domestiques, soldats, marins, détenus, mendiants, bohémiens, migrants, marginaux, and notables*.</footnote>

<footnote n="60">⁶⁰ See Appendix Table A26 for the distribution of the social categories variable.</footnote>

<footnote n="61">⁶¹ The original terminology of notables is *seigneur, noble, officier civil or magistrat, gens de loi or avocat, curé or vicaire or religieux, représentant du pouvoir municipal, roturier fortuné, cabaretier, personnage occulte, and autres*.</footnote>
of cases), members of a religious order (4 percent), and wealthy commoners (4 percent).<fnref n="62" />

### 3.1.5. Forms of Confrontation

The fifth set of variables concerns the forms of confrontation during rebellions: the modes of expression of rioters and whether they used weapons or uttered insults. Because these elements are composed of several not mutually exclusive categories, I create an indicator variable for each category that takes the value of 1 if that category is mentioned in the rebellion record.

**Modes of expression.** Rebellion records provide (limited) information on the modes of expression of rioters, across 4 categories: whether they used a tocsin, masks, cross-dressing or disguises, or musical instruments. Among the 7 percent of records that mention at least one mode of expression, the most frequently mentioned is the use of a tocsin (4 percent of cases).<fnref n="63" />

**Weapons.** The types of weapons used by rioters are documented in 60 percent of cases, across 7 categories: rocks, sticks or bars, tools, knives, firearms, other weapons, and no weapons. The most frequently mentioned types of weapons are sticks or bars (29 percent), rocks (21 percent), and knives (17 percent).<fnref n="64" />

**Insults.** The types of insults uttered by rioters are documented in 31 percent of cases, across 4 categories: sexual slurs, social slurs, slurs with double reference, and threats of bloodshed. The most frequently mentioned type of insult is threats of bloodshed (23 percent of cases).<fnref n="65" />

### 3.1.6. Forms of Violence

The sixth set of variables concerns the forms of violence in rebellions: against rioters, their adversaries, goods, and buildings. As before, these elements are composed of several not mutually exclusive categories, so I create an indicator variable for each category that takes the value of 1 if that category is mentioned in the rebellion record.

**Violence against rioters.** The forms of violence against rioters are documented in 35 percent of cases, across 6 categories: whether some rioters were wounded, killed, captured, captured then released, arrested after the confrontation, or imprisoned. The most frequently mentioned form

<footnote n="62">⁶² See Appendix Table A27 for the distribution of the notables involvement variable.</footnote>

<footnote n="63">⁶³ See Appendix Table A28 for the distribution of the modes of expression variable.</footnote>

<footnote n="64">⁶⁴ See Appendix Table A29 for the distribution of the weapons variable.</footnote>

<footnote n="65">⁶⁵ See Appendix Table A30 for the distribution of the insults variable.</footnote>
of violence is the capture of rioters during the confrontation (12 percent of cases). In addition, rebellion records sometimes include information on the number of rioters affected by each form of violence.<fnref n="66" />

**Violence against rioters' adversaries.** The forms of violence against rioters' adversaries are documented in 49 percent of cases, across 9 categories: whether some adversaries were disheveled, had their clothing torn, were disarmed, detained, run off, wounded, killed, whether their corpses were desecrated, and whether there were exchanges of blows. The most frequently mentioned forms of violence are that rioters' adversaries were run off (22 percent of cases), wounded (20 percent), and subject to exchanges of blows (12 percent). In addition, rebellion records sometimes include information on the number of rioters' adversaries affected by each form of violence.<fnref n="67" />

**Violence against goods.** The forms of violence against goods are documented in 23 percent of cases, across 17 categories: whether documents were burnt, stolen, or torn, whether posters were torn; whether buildings were stoned, invaded, demolished, or burnt, whether fences were broken or ditches filled, whether wood was looted from the forest, whether harvests were damaged, livestock attacked, and whether merchandise was misappropriated, looted, destroyed, burnt, or taxed. The most frequently mentioned form of violence against goods is the looting of merchandise (8 percent of cases).<fnref n="68" />

**Types of buildings attacked.** Finally, the types of buildings attacked by rioters are documented in 15 percent of cases, across 5 categories: seats of a public authority, seigneurial or nobiliary authority, ecclesiastical authority, and the homes of a local officer or notable. The most frequently mentioned type of building attacked is the home of a notable (7 percent of cases).<fnref n="69" />

### 3.1.7. Legal Consequences

The seventh set of variables concerns the legal consequences of rebellions: the jurisdictions that handled each case and the nature of sentencing. As before, these elements are composed of several not

<footnote n="66">⁶⁶ See Appendix Tables A31 and A32 for the distributions of the forms of violence against rioters variables.</footnote>

<footnote n="67">⁶⁷ See Appendix Tables A33 and A34 for the distributions of the forms of violence against adversaries variables.</footnote>

<footnote n="68">⁶⁸ See Appendix Tables A35 and A36 for the distribution of the violence against goods variable.</footnote>

<footnote n="69">⁶⁹ See Appendix Table A37 for the distribution of the types of buildings attacked variable.</footnote>
mutually exclusive categories, so I create an indicator variable for each
category that takes the value of 1 if that category is mentioned in the
rebellion record.

**Jurisdictions.** The jurisdictions that handled the rebellion's legal consequences are documented in 40 percent of cases, across 4 categories: simple seigneurial or royal jurisdictions, *bailliages, sénéchaussées, or présidiaux*, Parliaments or other sovereign courts, *prévôtés or maréchaussées*. The most frequently mentioned types of jurisdictions are *prévôtés or maréchaussées* (13 percent of cases), *bailliages, sénéchaussées, or présidiaux* (12 percent), and Parliaments or other sovereign courts (10 percent).<fnref n="70" />

**Sentencing.** The forms of sentencing for rioters are documented in 19 percent of cases, across 9 categories: sentencing to breaking on the wheel, to hanging, to the galleys (either for life or for a fixed term), to banishment, to the pillory or whip, to a fine, to a reprimand, or to prison. The most frequently mentioned type of sentencing is a fine (7 percent of cases). In addition, rebellion records sometimes include information on the number of rioters affected by each form of sentencing.<fnref n="71" />

3.1.8. Sources

The events dataset contains a few variables extracted from the sources
dataset, which provides detailed information on the sources used to create
rebellion records (see Section 3.2): the number of sources used to create a
given rebellion record, also broken down between archival and
bibliographic sources, and indicator variables that take the value of 1 if a
record cites at least one bibliographic source, one archival source,
one national archival source, or one local archival source. <fnref n="72" /> All but
six rebellion records have at least one source mentioned. On average,
rebellion records cite 1.3 sources, with archival sources being four times
more frequent than bibliographic ones. In addition, 87 percent of records
mention at least one archival source—with 47 percent mentioning at least

<footnote n="70">⁷⁰ See Appendix Table A38 for the distribution of the jurisdictions variable.</footnote>

<footnote n="71">⁷¹ See Appendix Tables A39 and A42 for the distributions of the sentencing variables.</footnote>

<footnote n="72">⁷² See Appendix Table A43 and A44. National archival sources are those from the National archives, the Bibliothèque nationale de France, the Service historique de la Défense, the archives of the préfecture of Police of Paris, the central archives of the Marine, the diplomatic archives, and the library of the Assemblée nationale. Local archival sources are those from départemental archives, municipal archives, municipal libraries, the Archivio di Stato di Torino, and the Bibliothèque historique de la Ville de Paris.</footnote>
one national archival source and 42 percent, at least one local archival
source—and 21 percent, at least one bibliographic source.

Based on the source composition of each record, I create a département-
level quality grade variable that characterizes each record—the
methodology of this grading scheme is detailed in Section 4.2.4. Grades
range from higher quality (grade A) to lower quality (grade D). They are
available for all records that describe rebellions that occurred on the current
territory of France, i.e., all but 9 records. About one third of records have
the grade of A (34 percent), another third, the grade of B (34 percent), and
the rest, the grades of C (18 percent) and D (14 percent).<fnref n="73" />

3.1.9. Authorship

The events dataset provides a few variables extracted from the authors
dataset, which provides detailed information on the researchers who
created rebellion records (see Section 3.3): the identifier and name of the
author of each record. A total of 64 authors contributed to the Jean Nicolas
survey. Jean Nicolas himself produced 5,200 records (61 percent) of the
events dataset. Several other authors also made substantial contributions:
Sylvie Kleiber produced 351 records (4 percent), Elie Pélaquier, 309
records (4 percent), and Francis Loirette, 248 records (3 percent). In total,
16 authors contributed at least 70 records.<fnref n="74" />

3.1.10. Description of Events

The final and tenth set of variables provides a description of the event in
two ways: first, the terms used by contemporaries to characterize the
rebellion—available under the label “Movement’s characterization by
contemporaries” (“Qualification du mouvement par les contemporains”)—
and second, a textual description—available under the label “Other
information” (“Autres informations”).

**Terminology used by contemporaries.** The terms used by contemporaries are not mutually exclusive, so I create an indicator variable for each category that takes the value of 1 if that term is mentioned in the rebellion record. A terminology is documented in 54 percent of cases, with an average of 1.7 terms. I report the mention of 27 different terms that appear in at least 10 records: “rebellion,” “gathering,” “sedition,” “emotion,” “riot,” “tumult,” “disorder,” “excess,” “revolt,” “troubles,” “mutiny,” “assembly,” “violence,” “uprising,” “movement,” “carillon,” “rumor,” “cabal,”

<footnote n="73">⁷³ See Appendix Table A54 for the distribution of the grade variable. Appendix Figure A26 provides its spatial distribution.</footnote>

<footnote n="74">⁷⁴ See Appendix Table A45 for the distribution of the authorship variable. The events dataset also provides the identifier of the research assistant who input the content of each record.</footnote>
"conspiracy," "noise," "murmurs," "tapage," "brawl," "insurrection," "battery,"
"hullabaloo," and "effervescence."<sup>75</sup> The most frequently mentioned terms
are "rebellion" (21 percent of records), "gathering" (11 percent), "sedition"
(9 percent), "emotion" (9 percent), and "riot" (8 percent).<sup>76</sup>

**Textual description.** The textual description of events is available for 7,974 records (94 percent).<sup>77</sup> It is provided in the form of a long string, up to 9,491 characters long.

3.2. The Sources Dataset

The sources dataset (*nicolas.sources*) provides detailed information on
the sources of records in the events dataset. It is a record-source-level
dataset with 10,747 observations, where each source has a unique source
identifier. This dataset can be matched to the events dataset through the
*nicolas* identifiers. Each source is classified either as an archival source
(80 percent of cases) or a bibliographic source (20 percent). The original
source strings as transcribed from rebellion records are also included.<sup>78</sup> The
22 variables included in the sources dataset are listed in Panel B of
Appendix Table A1.

3.2.1. Archival Sources

Archival sources are further classified across 12 holding services—this
information is available for all but 22 archival sources.<fnref n="79" /> Archival sources
are drawn primarily from the National (43 percent of archival sources) and
départemental (40 percent) archives. I also provide the main archival series

<footnote n="75">⁷⁵ The original terminology of these terms is rébellion, attroupement, sédition, émotion, émeute, tumulte, désordres, excès, révolte, troubles, mutinerie, assemblée, violences, soulèvement, mouvement, carillon, rumeur, cabale, complot, bruit, murmures, tapage, rixe, insurrection, batterie, charivari, and effervescence. I do not include the terms affrontements, rassemblement, révolution, agitation, commotion, crieries, fureur, or prise d'armes, since they appear in less than 10 records.</footnote>

<footnote n="76">⁷⁶ See Appendix Tables A40 and A41 for the distribution of the terms used by contemporaries.</footnote>

<footnote n="77">⁷⁷ These descriptions were entered by Renan Donnerh, the manager of the François Lebrun Library at the University of Rennes-2 where the Jean Nicolas records are preserved.</footnote>

<footnote n="78">⁷⁸ These strings were also entered by Renan Donnerh. Links to the original sources can be found in the url variables in the HiSCoD database (Chambru & Maneuvrier-Hervieu, 2024).</footnote>

<footnote n="79">⁷⁹ See Appendix Table A46 for the distribution of archival services.</footnote>
of sources from National and départemental archives.<fnref n="80" /> Among these,
28 percent are from the B series of départemental archives (Courts and
jurisdictions), 18 percent, from the Z1A series of the National archives
(Court of Aids of Paris), 17 percent, from the C series of départemental
archives (Provincial administrations), and 13 percent, from the G7 series of
the National archives (General control of finances). Finally, I provide
information on the location of each archive holding service in
2021 geography, including its *insee* and *ign* identifiers, commune's
toponymy, spatial coordinates, and administrative setting—region,
*département*, and *arrondissement* (see Section 4.2).

3.2.2. Bibliographic Sources

Bibliographic sources are classified into 4 categories: whether they
correspond to books (69 percent of bibliographic sources), journal articles,
book chapters, or conference proceedings (19 percent), master's theses
(9 percent), or dissertations (4 percent).

3.3. The Authors Dataset

The authors dataset (*nicolas_authors*) provides detailed information on
the 64 authors of records in the events dataset. Based on the content of
Jean Nicolas's logbook, it includes each author's minimum, maximum, and
average year of collaboration on the Jean Nicolas survey (available for
49 authors), as well as their professional location during this period in
2021 geography, with each author's location *insee* and *ign* identifier,
commune's toponymy, spatial coordinates, and administrative setting—
region and *département* (see Section 4.2). The 19 variables included in the
authors dataset are listed in Panel C of Appendix Table A1.

4. RELIABILITY OF THE JEAN NICOLAS DATABASE

This section evaluates the reliability of the Jean Nicolas database. First, I
compare the content of the database with the entries of the HiSCoD
database (Section 4.1). Then, I conduct a quantitative source criticism
exercise, analyzing potential biases introduced by the construction
methodology of the Jean Nicolas survey (Section 4.2). I also provide
recommendations on how to mitigate these biases for an empirical
exploitation of the Jean Nicolas database.

<footnote n="80">⁸⁰ See Appendix Table A47 for the distribution of archival series from National and départemental archives.</footnote>
## 4.1. Comparison with the HiSCoD Database

The Historical Social Conflict Database (HiSCoD) comprises about 21 thousand episodes of social conflict in Europe, spanning from the High Middle Ages to the late nineteenth century (Chambru & Maneuvrier-Hervieu, 2024). The Jean Nicolas survey is HiSCoD's most substantial data source, contributing 8,478 events—about 40 percent of the events in the HiSCoD database, and 54 percent of those located in France.<fnref n="81" />,<fnref n="82" /> While all but four Jean Nicolas records in HiSCoD are included in the *nicolas_events* dataset, 42 events included in the *nicolas_events* dataset are absent from HiSCoD.<fnref n="83" /> In addition, HiSCoD includes only a limited subset of variables for each rebellion—their typology, date, location, number and gender of participants, sources, and authorship. By contrast, the *nicolas_events* dataset retains the full set of variables available in each rebellion record, together with auxiliary data such as location population counts. An additional difference is that rebellion locations in the *nicolas_events* dataset are situated in both Ancien Régime and contemporary geographies, whereas HiSCoD locates them only in contemporary geography.

To assess the validity of the Jean Nicolas database, I compare its content with that of HiSCoD for the 8,477 rebellion records that are included in both databases.<fnref n="84" /> For each record, I match all variables that are common to both datasets and manually check the relevant original record whenever a discrepancy arises. The results of this comparison are reported in Table 2. This analysis draws on the *nicolas_hiscod* dataset, which includes the original variables from both HiSCoD and *nicolas_events* datasets, as well as flag variables indicating discrepancies—the 41 variables included in

<footnote n="81">⁸¹ This portion of the HiSCoD database was derived from Jean Nicolas's personal data file, which he used to produce his book (Nicolas, 2002) and shared with Cédric Chambru and Paul Maneuvrier-Hervieu in 2012. I am grateful to Cédric Chambru for bringing this information to my attention.</footnote>

<footnote n="82">⁸² Although Chambru and Maneuvrier-Hervieu (2024, Table 1, p. 1085) report that HiSCoD includes 8,528 events based on the Jean Nicolas survey, the corresponding CSV file *db_hiscod_csv_v1_fr*, accessed from github.com/hiscod/hiscod-project in November 2025, contains only 8,478 such events.</footnote>

<footnote n="83">⁸³ Of the four records present in HiSCoD but not in the *nicolas_events* dataset, one is an “effective” duplicate (4291), two are incomplete records (8780 and 8781), and one could not be located (8763). The reason for the absence of 42 records from HiSCoD remains unclear, as they do not appear to be duplicates.</footnote>

<footnote n="84">⁸⁴ This comparison includes the “effective” duplicate record (4291) and the two incomplete records (8780 and 8781), but excludes the record that could not be located (8763).</footnote>
the HiSCoD comparison dataset are listed in Panel D of Appendix Table A1. Overall, 1,619 HiSCoD records (19 percent) contain at least one error.

<table><caption>Table 2 – Comparison with the HiSCoD Database.</caption><thead><tr><th rowspan="2"></th><th colspan="2">Variable names</th><th colspan="2">Errors in HiSCoD</th></tr><tr><th>nicolas_events</th><th>HiSCoD</th><th>Freq.</th><th>Percent</th></tr></thead><tbody><tr><td>Nicolas identifier</td><td>nicolas</td><td>id_riotspanner_databa</td><td>7</td><td>0.08</td></tr><tr><td>Primary type</td><td>typePrim_d</td><td>riot_typeOriginal_databa_1</td><td>469</td><td>5.53</td></tr><tr><td>Secondary type</td><td>typeSec_d</td><td>riot_typeOriginal_databa_2</td><td>1,152</td><td>13.59</td></tr><tr><td>Date</td><td>date</td><td>year, month_num, day</td><td>123</td><td>1.45</td></tr><tr><td>Location (2021 geography)</td><td>insee_2021</td><td>city_code</td><td>35</td><td>0.41</td></tr><tr><td>Number of participants</td><td>part_nb</td><td>nb_participants</td><td>98</td><td>1.16</td></tr><tr><td>Gender of participants</td><td>part_women</td><td>women_participation</td><td>152</td><td>1.79</td></tr><tr><td>Author</td><td>author</td><td>author</td><td>30</td><td>0.35</td></tr><tr><td>At least one error in HiSCoD</td><td></td><td></td><td>1,619</td><td>19.10</td></tr><tr><td>Total</td><td></td><td></td><td>8,477</td><td>100.00</td></tr></tbody></table>

Notes. This table reports the distribution of errors in HiSCoD for the overlapping set of events and variables in the *nicolas_events* dataset. It corresponds to the *nicolas_hisco*, *typePrim_d*, *typeSec_d*, *date_hisco*, *location_hisco*, *part_nb*, *part_women*, *author*, and *error_hisco* variables of the *nicolas_hisco* dataset.

First, 7 records contain incorrect record identifiers, typically due to typographical errors—such as entering “7774” instead of “7744.” Second, the typology variables exhibit a substantial number of errors: 469 records (6 percent) have errors in their primary types and 1,152 records (14 percent), in their secondary types. In total, 1,268 HiSCoD records (15 percent) contain at least one error in their typology.<fnref n="85" /> Third, 123 records include at least one error in the date variables, most of which concern the day component.<fnref n="86" /> Fourth, 35 records present errors in the rebellion locations—an additional 37 records display further discrepancies between the two databases, e.g., due to uncertainty regarding the original location or because the referenced location was created after 1793.<fnref n="87" /> Fifth, 98 records contain inaccuracies in the number of participants—an additional 257 records further display discrepancies between the two databases due to differences in the interpretation of participation counts, e.g., when reported

<footnote n="85">⁸⁵ Note that HiSCoD also contains an alternative typology along nine types (Chambru & Maneuvrier-Hervieu, 2024, Table 2, p. 1086). However, Chambru and Maneuvrier-Hervieu (2024, p. 1086) “highlight here that [their] classification is first and foremost intended as a tool to guide users through the myriad of events reported. One can use the various information included in the database to establish her own typology and/or assign several categories to an event.”</footnote>

<footnote n="86">⁸⁶ See Appendix Table A48 for the distribution of the date comparison variable.</footnote>

<footnote n="87">⁸⁷ See Appendix Table A49 for the distribution of the location comparison variable.</footnote>
as intervals rather than precise numbers.<fnref n="88" /> Sixth, 152 records include errors regarding the gender of participants.<fnref n="89" /> Finally, 30 records have incorrect author information—an additional 91 records further display discrepancies between the two databases due to typographical errors in author names, e.g., “Serge Dotenwill” instead of “Serge Dontenwill” or “Nicole Postel-Pellegrin” instead of “Nicole Pellegrin-Postel.”

## 4.2. Biases in the Jean Nicolas Survey

A key concern is whether rebellions included in the Jean Nicolas survey can be considered as representative both temporally (Figure 1) and spatially (Figure 2). Several potential biases remain challenging to assess without extensive historical and archival research, particularly those stemming from the destruction, gaps, and reliability of archival sources (Nicolas, 2002, p. 15). Additionally, the observed upward trend in rebellions starting in the 1740s might reflect changes in state actors’ recording practices or their enhanced capacity for repression associated with state consolidation during this period (see, e.g., Albertus & Gay, 2025).

Nevertheless, certain biases resulting from the survey methodology can be systematically evaluated. This section focuses specifically on three types of biases: those related to the selection of sources used to compile rebellion records (Section 4.2.1), those associated with the authorship of these records (Section 4.2.2), and those stemming from the incomplete examination of local archives (Section 4.2.3). After systematically exploring these biases and recommending strategies to mitigate them, this section introduces a département-level grading scheme that summarizes the quality of rebellion records in the Jean Nicolas database (Section 4.2.4).

### 4.2.1. Source-Driven Biases

Rebellion records draw on a wide range of sources, each with distinct characteristics that may introduce systematic biases into the temporal, spatial, and typological distribution of recorded events. I examine three primary dimensions of source variation: first, the difference between archival and bibliographic sources; second, the distinction between national and local archival materials; and third, the influence of specific recording actors, reflected in the sources’ archival series.

**Archival and bibliographic sources.** The broad type of sources used to compile rebellion records may influence their temporal and spatial distribution. Indeed, records based exclusively on archival sources display

<footnote n="88">⁸⁸ See Appendix Table A50 for the distribution of the number of participants comparison variable.</footnote>

<footnote n="89">⁸⁹ This variable is constructed following the method described in Chambru and Maneuvrier-Hervieu (2024, Appendix, pp. 4–5). See Footnote 57.</footnote>
time patterns similar to those observed in the full dataset (Figure 4). By contrast, records based exclusively on bibliographic sources show notable differences. In particular, they fail to capture the 1709 surge in rebellion activity and the upward trends in rebellion beginning in the 1740s.

Similarly, the spatial distribution of rebellions based on archival sources closely mirrors that of the full dataset (Panel a of Figure 5). By contrast, rebellions drawn from bibliographic sources exhibit much more clustered spatial patterns, likely reflecting their reliance on regional monographs (Panel b of Figure 5). For instance, the cluster of approximately 60 rebellions in the Cévennes region—located in the southeast of the Massif Central—is largely attributable to the reliance on Bosc's (1985–93) comprehensive study of the War of the Camisards.

<figure><img src="image_6.png" /><figcaption>Figure 4 – Temporal Distribution of Rebellions by Type of Sources.</figcaption></figure>

*Notes.* This figure displays the temporal distribution of rebellions by type of sources in the events dataset based on the *date_year* variable. The black dotted line includes the 8,510 rebellions with at least one source mentioned; the blue line, the 6,718 rebellions with exclusively archival sources; and the red line, the 1,113 rebellions with exclusively bibliographic sources.

**National and local archival sources.** The origin of archival sources— whether national or local—can also affect the temporal and spatial distribution of rebellions, as these sources may capture events of different scales or reflect the perspectives of distinct sets of actors. Reassuringly, both types of records exhibit time patterns closely aligned with those of the full dataset—though the 1709 surge in rebellion activity is not so pronounced for records drawing on local archival sources (Figure 6).
Nevertheless, the spatial distribution of rebellions differs somewhat between the two types of archival sources. National archival sources capture rebellions relatively evenly across the territory, particularly along the boundaries of the Grandes Gabelles frontiers in the northwest and in the north (Panel a of Figure 7).<fnref n="90" /> This broader coverage is likely due to the archives of the Ferme Générale—the institution that managed the *gabelle* salt taxation—being preserved in the National Archives under the archival series of the Court of Aids (AN-Z1A). By contrast, local archival sources reveal more clustered patterns: rebellion records are for instance relatively dense in southern Brittany and eastern Languedoc but essentially absent in northeastern France (Panel b of Figure 7). As discussed in Section 4.2.2, such patterns of rebellions drawing on local archival sources are likely driven by the regional stratification of collaborators to the Jean Nicolas survey.

<figure><img src="image_7.png" /><figcaption>Figure 5 – Spatial Distribution of Rebellions by Type of Sources.</figcaption></figure>

*Notes.* This figure displays the spatial distribution of rebellions by type of sources in RGF93 projection. Panel a includes the 6,718 rebellions with exclusively archival sources, and Panel b, the 1,113 rebellions with exclusively bibliographic sources. The underlying shapefile of the Kingdom of France as of 1789 is based on Gay et al.'s (2023) jurisdictions shapefile (Gay et al., 2024). The underlying shapefile of France as of 2021 is based on IGN's (2021) ADMIN-EXPRESS shapefile.

**Types of archival series and recording actors.** A third type of source-
driven bias may stem from the over-representation of some archival

<footnote n="90">⁹⁰ Rebellions primarily motivated by salt smuggling—type 0204—account for 24 percent of all recorded rebellions (2,065 cases) in the events dataset (Appendix Table A3). Among these, 76 percent rely on sources drawn from national archival sources, compared to only 18 percent from local archival sources.</footnote>
series—reflecting different actors with heterogeneous recording practices and repression capacity—in the documentation of certain types of rebellions. To highlight this potential source of bias, I focus on the three main types of rebellions: rebellions linked to resistance to state taxation (3,380 cases), those linked to resistance to the state judiciary, military, or police (2,242 cases), and those linked to subsistence motives (1,510 cases).<fnref n="91" /> I find that some archival series account for a disproportionate share of rebellion records within these types.<fnref n="92" /> For instance, the (national) archives of the Court of Aids (AN-Z1A) account for one third of rebellions involving resistance to state taxation. Likewise, the (départemental) archives of courts and jurisdictions (AD-B) account for one quarter of rebellions involving resistance to the state judiciary, military, or police.

<figure><img src="image_8.png" /><figcaption>Figure 6 – Temporal Distribution of Rebellions by Type of Archival Sources.</figcaption></figure>

*Notes.* This figure displays the temporal distribution of rebellions by type of archival sources in the events dataset based on the *date_year* variable. The black dotted line includes the 6,718 rebellions with exclusively archival sources; the blue line, the 3,556 rebellions with exclusively national archival sources; and the red line, the 3,045 rebellions with exclusively local archival sources.

Given these considerations, researchers using the Jean Nicolas database
should carefully assess the robustness of their results to these potential

<footnote n="91">⁹¹ These figures are larger than those displayed in either column of Table 1 because they comprise both primary and secondary types. Moreover, they only concern rebellions that mention at least one archival source.</footnote>

<footnote n="92">⁹² See Appendix Table A51 for the distribution of the main archival series type of rebellion.</footnote>
biases. Proper guidelines include excluding rebellion records that rely exclusively on bibliographic sources, contrasting results across rebellion records that draw on national and local archival sources, and ensuring that findings are not disproportionately driven by any single archival series.

<figure><img src="image_9.png" /><figcaption>Figure 7 – Spatial Distribution of Rebellions by Type of Archival Sources.</figcaption></figure>

*Notes.* This figure displays the spatial distribution of rebellions by type of archival sources in RGF93 projection. Panel a includes the 3,556 rebellions with exclusively national archival sources, and Panel b, the 3,045 rebellions with exclusively local archival sources. The underlying shapefile of the Kingdom of France as of 1789 is based on Gay et al.'s (2023) jurisdictions shapefile (Gay et al., 2024). The underlying shapefile of France as of 2021 is based on IGN's (2021) ADMIN-EXPRESS shapefile.

### 4.2.2. Author-Driven Biases

Another set of biases may arise from the authorship of rebellion records. I first examine differences in rebellion patterns across records authored by Jean Nicolas compared to his collaborators, then show that authors' workplace locations may introduce biases in the spatial distribution of recorded rebellions.

**Jean Nicolas and his collaborators.** While Jean Nicolas personally authored 61 percent of the records in the survey (5,200 cases), the remaining entries were contributed by 63 different collaborators (3,316 cases). Both types of records exhibit similar time patterns, aligned with those of the full dataset—though rebellion records authored by Jean Nicolas's collaborators exhibit a dip in the 1780s. However, the spatial distribution of rebellion records authored by Jean Nicolas differs from that
of records authored by his collaborators.<fnref n="93" /> Specifically, the patterns of
rebellion records authored by Jean Nicolas resemble a combination of the
patterns seen in records based on bibliographic and national archival
sources, while those authored by his collaborators align more closely with
records based on local archival sources.

These discrepancies can be explained by the types of sources used by Jean Nicolas compared to his collaborators. Jean Nicolas drew on both archival and bibliographic sources: among the records he authored, 81 percent cite at least one archival source, and 26 percent, at least one bibliographic source. By contrast, his collaborators relied more heavily on archival sources. Of the records they authored, 96 percent cite at least one archival source, while only 13 percent cite at least one bibliographic source. In addition, the archival material used by Jean Nicolas was primarily located in institutions near his home university in Paris: 69 percent of the records he authored cite sources from the National archives, and 9 percent, sources from the Bibliothèque nationale de France. By contrast, archival sources of his collaborators were predominantly local, with 71 percent of their archival-based records drawing on archival services located within the département of their place of work—a figure that rises to 92 percent when considering archival services located within their broader region.<fnref n="94" />

Hence, to alleviate this potential source of bias, researchers using the Jean
Nicolas database should assess the robustness of their results by
contrasting them across rebellion records authored by Jean Nicolas and his
collaborators.

**Regional stratification of the survey.** Another type of bias may arise from the regional stratification of the Jean Nicolas survey. As discussed in Section 2.1.2, Jean Nicolas recruited his collaborators to cover specific geographic areas—generally, the département of their places of work. This recruitment process led to a pattern of spatial proximity between the workplace locations of these collaborators and the rebellion records they authored (Panel a of Figure 8).<fnref n="95" /> Notable gaps in coverage are evident, similar to those highlighted in Section 4.2.1. For instance, the Grand Est region—highlighted in the northeast of the map—is strikingly underrepresented in the set of records collected by Jean Nicolas’s

<footnote n="93">⁹³ See Appendix Figures A22 and A23 for the temporal and spatial distributions of authorship.</footnote>

<footnote n="94">⁹⁴ Excluding sources drawn from the National archives and the Bibliothèque nationale de France, these proportions increase to 76 and 94 percent, respectively.</footnote>

<footnote n="95">⁹⁵ This map only shows rebellion records drawing on local archival sources and authored by Jean Nicolas’s collaborators.</footnote>
collaborators.<fnref n="96" /> This gap does not necessarily imply a lack of rebellious activity in the region (see, e.g., Bischoff, 2009; Cabourdin, 1977; Gallet, 2009), but rather reflects the fact that the local archives of this region were seldom explored because Jean Nicolas was largely unsuccessful in recruiting collaborators in this area—this was not for a lack of effort on the part of Jean Nicolas, as his logbook reveals that he made 83 unsuccessful attempts at recruiting local collaborators throughout his survey. In the case of the Grand Est region, he reached out to 14 potential collaborators but only received two affirmative responses. The distribution of these unsuccessful contact attempts documented in his logbook is shown in Panel b of Figure 8.

<figure><img src="image_10.png" /><figcaption>Figure 8 – Spatial Distribution of Rebellions by Type of Collaborator.</figcaption></figure>

Notes. This figure displays the spatial distribution of rebellions by type of collaborator in RGF93 projection. Panel a includes Jean Nicolas's 63 collaborators based on their workplace at the time of their collaboration on the Jean Nicolas survey, and Panel b, the 83 researchers who were contacted by Jean Nicolas but who ultimately did not collaborate in the survey. The spatial distribution of rebellions corresponds to the 2,444 records authored by Jean Nicolas's collaborators that draw exclusively on local archival sources. The highlighted area corresponds to the Grand Est region. The underlying shapefile of the Kingdom of France as of 1789 is based on Gay et al.'s (2023) jurisdictions shapefile (Gay et al., 2024). The underlying shapefile of France as of 2021 is based on IGN's (2021) ADMIN-EXPRESS shapefile.

<footnote n="96">⁹⁶ This region comprises 10 départements: Ardennes, Aube, Marne, Haute-Marne, Meurthe-et-Moselle, Meuse, Moselle, Bas-Rhin, Haut-Rhin, and Vosges. Only 4 rebellion records authored by Jean Nicolas's collaborators drawing exclusively on local archival sources fall in this area, for a total of 419 rebellion records (5 percent) in the full dataset.</footnote>
This intuition is supported by a statistical analysis. Specifically, I examine whether the likelihood of observing a rebellion in a parish increases with proximity to the nearest collaborator of Jean Nicolas—I use the framework of Ancien Régime parishes. As shown in Figure 9, the probability of observing a rebellion decreases linearly with distance from the nearest collaborator. Focusing on rebellion records authored by collaborators and drawing exclusively on local archival sources—represented by red dots— the likelihood of observing a rebellion approaches zero when no collaborator is located within 75 kilometers.

To assess the magnitude of this spatial bias, I investigate this pattern through a regression analysis. Specifically, I estimate the following linear regression model:

$$ (1) \quad \text{Rebellion}_p = \alpha + \beta \log \text{Distance}_p + \mathbf{X}'_p \theta + \varepsilon_p, $$

where Rebellionₚ denotes an indicator variable that takes the value of 1 if parish p ever hosted a rebellion between 1661 and 1789, and Distanceₚ, the distance to the nearest collaborator—or unsuccessful contact—of Jean Nicolas, in kilometers.<fnref n="97" /> Of course, universities of Jean Nicolas's collaborators are generally located in urban centers, where the incidence of rebellions was presumably higher. Hence, vector X controls for parishes population in 1793 and for their representation on Cassini's map, included as fixed effects.<fnref n="98" /> To account for spatial clustering arising from both the local co-occurrence of rebellions and the survey's regional stratification, I cluster standard errors at the level of départements.

I report the results in Columns 1–4 of Table 3. In Panel A, I focus on all rebellion records. The coefficient in Column 1 is statistically significant at the one percent level and implies that a 10 percent increase in the distance to the nearest collaborator is associated with a small decrease in the probability of observing a rebellion of 0.4 percentage point. This coefficient remains stable after controlling for the distance to the nearest unsuccessful contact (Column 3) and parish-level characteristics (Column 4). Results are similar in Panel B when restricting the sample of rebellion records to those authored by collaborators and drawing exclusively on local archival sources, though the relationship is weaker by a factor of one quarter. These results highlight the slight spatial dependence between the location of Jean

<footnote n="97">⁹⁷ I use the log transformation of the distance measure because it approximates a normal distribution more closely than the untransformed measure, which resembles a right-skewed χ distribution (Appendix Figure A24).</footnote>

<footnote n="98">⁹⁸ This vector also controls for the spatial coordinates of parishes to account for the local topography that may affect both the incidence of rebellion and the density of the urban landscape</footnote>
Nicolas's collaborators and the likelihood of observing a rebellion, suggesting that researchers using the Jean Nicolas survey should be mindful of its spatial representativeness.

<figure><img src="image_11.png" /><figcaption>Figure 9 – Incidence of Rebellions and Distance to Nearest Collaborator.</figcaption></figure>

*Notes.* This figure displays the relationship between the incidence of rebellions and the distance to the nearest collaborator of Jean Nicolas in kilometers. Each dot represents an equal-size bin of about two thousand parishes. Figure generated using Stepner's (2013) *binscatter Stata* command.

Reassuringly, this modest spatial bias substantially diminishes once the survey's regional stratification is accounted for: including 94 département fixed effects reduces the correlation by more than one half (Panel A, Column 5) and by one third when focusing on rebellion records authored by collaborators (Panel B, Column 5). This suggests that the Jean Nicolas survey may be considered close to spatially representative for *within-département* comparisons. I therefore recommend that practitioners include département fixed effects when conducting empirical analyses using the Jean Nicolas database.<fnref n="99" />

<footnote n="99">⁹⁹ In doing so, and depending on the outcome of interest, practitioners should be mindful of the potential post-treatment bias introduced by controlling for twentieth-century département heterogeneity (Homola et al., 2024).</footnote>
<table><caption>Table 3 – Incidence of Rebellions and Distance to Nearest Collaborator.</caption><thead><tr><th></th><th colspan="5">Outcome: Indicator for rebellion in 1661–1789</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th></tr></thead><tbody><tr><td colspan="6">A. All rebellion records (8,508 cases over 4,264 parishes)</td></tr><tr><td>Log distance to nearest collaborator (km)</td><td>-0.041***<br>[0.010]</td><td>-0.040***<br>[0.010]</td><td>-0.041***<br>[0.008]</td><td>-0.016**<br>[0.007]</td><td></td></tr><tr><td>Log distance to nearest unsuccessful contact (km)</td><td></td><td>-0.009<br>[0.009]</td><td>-0.002<br>[0.009]</td><td>0.012<br>[0.007]</td><td>0.009<br>[0.006]</td></tr><tr><td>Parishes</td><td>40,415</td><td>40,415</td><td>40,415</td><td>39,604</td><td>39,604</td></tr><tr><td>R-squared</td><td>0.008</td><td>0.000</td><td>0.008</td><td>0.160</td><td>0.197</td></tr><tr><td colspan="6">B. Rebellion records by collaborators drawing on local archives (2,443 cases over 1,435 parishes)</td></tr><tr><td>Log distance to nearest collaborator (km)</td><td>-0.029***<br>[0.006]</td><td>-0.028***<br>[0.005]</td><td>-0.030***<br>[0.005]</td><td>-0.020***<br>[0.005]</td><td></td></tr><tr><td>Log distance to nearest unsuccessful contact (km)</td><td></td><td>-0.012**<br>[0.006]</td><td>-0.006<br>[0.005]</td><td>0.003<br>[0.005]</td><td>0.006<br>[0.005]</td></tr><tr><td>Parishes</td><td>40,415</td><td>40,415</td><td>40,415</td><td>39,604</td><td>39,604</td></tr><tr><td>R-squared</td><td>0.011</td><td>0.002</td><td>0.011</td><td>0.083</td><td>0.129</td></tr><tr><td>Controls</td><td>No</td><td>No</td><td>No</td><td>Yes</td><td>Yes</td></tr><tr><td>Département fixed effects (94)</td><td>No</td><td>No</td><td>No</td><td>No</td><td>Yes</td></tr></tbody></table>

*Summary statistics.* Incidence of all rebellions: 0.105 (mean), 0.306 (s. d.). Incidence of rebellions by collaborators drawing on local archives: 0.035 (mean), 0.184 (s. d.). Distance to nearest collaborator: 57 (mean), 36 (s. d.). Distance to nearest unsuccessful contact: 59 (mean), 32 (s. d.).

*Notes.* This table reports the OLS coefficients from estimating Equation 1. The unit of observation is a parish. Controls include parish population in 1793, parish representations in Cassini's map under the form of fixed effects, and parish spatial coordinates. Estimates are calculated using Correia's (2023) *reghdfe* Stata command. Standard errors are clustered at the département level and reported in brackets. *Statistical significance.* ***$p \le 0.01$. **$p \le 0.05$. *$p \le 0.10$.

### 4.2.3. Incomplete Examination of Local Archival Sources

Despite the (limited) spatial biases documented in Sections 4.2.1 and 4.2.2, the Jean Nicolas database still reveals notable gaps in the recording of rebellions *within* certain localized regions. To highlight this additional potential source of bias, this section develops a case study on two départements in the region of Eastern Brittany.

Eastern Brittany presents a striking contrast in recorded rebellious activity. In the département of Loire-Atlantique, 418 rebellions are recorded, while in the neighboring Ille-et-Vilaine, only 100 appear in the database.<fnref n="100" /> Yet in 1793, both départements had comparable populations: 416 thousand in

<footnote n="100">¹⁰⁰ See Appendix Figure A25. In fact, after Paris, the département of Loire-Atlantique is the one with the most rebellion records in the Jean Nicolas database.</footnote>
Loire-Atlantique and 511 thousand in Ille-et-Vilaine. This disparity raises an important question: does it reflect actual differences in levels of unrest, or does it instead point to inconsistencies in the underlying data collection process?

A close analysis of authorship and sources points to the latter explanation (Table 4). Most of the rebellion records for Loire-Atlantique (82 percent) were produced by Sylvie Kleiber during her master's thesis—written under the supervision of Jean Nicolas. She relied primarily on départemental archives, systematically examining the B series of judicial court records, which accounts for 74 percent of the archival sources cited for this département. By contrast, no researcher focused specifically on Ille-et-Vilaine: Jean Nicolas himself produced the majority of its records (77 percent), drawing heavily on secondary sources (33 percent) and relying on national archives for nearly half (45 percent) of the cited archival sources. Although Isabelle Coulange—another of Nicolas's students—consulted the B series of Ille-et-Vilaine's départemental archives, her survey was limited to a narrow period (1700–40), resulting in a limited coverage (20 rebellion records).

To assess the magnitude of the bias resulting from the incomplete survey of local archives in Ille-et-Vilaine, Brice Évain (2022) conducted a systematic review of the entire B series at the départemental archives of this département.<fnref n="101" />,<fnref n="102" /> Applying the same criteria used in the original Jean Nicolas survey, he identified 87 additional rebellions—nearly doubling the initially recorded number of rebellions for this département.<fnref n="103" /> These findings indicate that about one-third of the discrepancy in recorded rebellions between Loire-Atlantique and Ille-et-Vilaine results from the limited examination of local archival sources. A proper exploitation of the Jean Nicolas database thus requires careful attention to the relative weight of local archives in the sources cited in rebellion records.

#### 4.2.4. Département-Level Grading Scheme

Based on these findings, I propose a département-level grading scheme designed to summarize the quality of rebellion records in the Jean Nicolas database—it focuses on the département level due to the nature of the survey's stratification. This grading scheme retains three criteria aimed at capturing source- and author-driven biases: the share of rebellion records

<footnote n="101">¹⁰¹ This research was funded by the ANR-20-CE38-001 (ObARDI) grant and carried out during Summer 2022 with assistance from three master's students: Alix Janvier, Delphine Mialot, and Alicia Riou.</footnote>

<footnote n="102">¹⁰² A similar analysis can be conducted for Normandy, drawing on Maneuvrier-Hervieu's (2020) comprehensive survey of subsistence riots from 1709 to 1817.</footnote>

<footnote n="103">¹⁰³ See Appendix Figure A25 and Table 4.</footnote>
in a département citing at least one départemental archival source, the share citing at least one bibliographic source, and an indicator variable that takes the value of 1 if a collaborator was based in the département.<fnref n="104" />

<table><caption>Table 4 – Breton Rebellions in the Jean Nicolas and Brice Évain Surveys.</caption><thead><tr><th rowspan="3"></th><th colspan="4">Nicolas survey</th><th colspan="2">Evain survey</th></tr><tr><th colspan="2">Loire-Atlantique</th><th colspan="2">Ille-et-Vilaine</th><th colspan="2">Ille-et-Vilaine</th></tr><tr><th>Freq.</th><th>Percent</th><th>Freq.</th><th>Percent</th><th>Freq.</th><th>Percent</th></tr></thead><tbody><tr><td colspan="7"><strong>Authors</strong></td></tr><tr><td>NICOLAS Jean</td><td>50</td><td>11.96</td><td>77</td><td>77.00</td><td></td><td></td></tr><tr><td>COLLARD Nicole</td><td>13</td><td>3.11</td><td>2</td><td>2.00</td><td></td><td></td></tr><tr><td>COULANGE Isabelle</td><td>14</td><td>3.35</td><td>20</td><td>20.00</td><td></td><td></td></tr><tr><td>KLEIBER Sylvie</td><td>341</td><td>81.58</td><td>1</td><td>1.00</td><td></td><td></td></tr><tr><td>EVAIN Brice</td><td></td><td></td><td></td><td></td><td>87</td><td>100.00</td></tr><tr><td>Rebellion records</td><td>418</td><td>100.00</td><td>100</td><td>100.00</td><td>87</td><td>100.00</td></tr><tr><td colspan="7"><strong>Type of sources</strong></td></tr><tr><td>Archive</td><td>434</td><td>94.76</td><td>91</td><td>66.91</td><td>93</td><td>88.57</td></tr><tr><td>Bibliography</td><td>24</td><td>5.24</td><td>45</td><td>33.09</td><td>12</td><td>11.43</td></tr><tr><td>Sources</td><td>458</td><td>100.00</td><td>136</td><td>100.00</td><td>105</td><td>100.00</td></tr><tr><td colspan="7"><strong>Archival service</strong></td></tr><tr><td>National archives</td><td>59</td><td>13.59</td><td>41</td><td>45.05</td><td></td><td></td></tr><tr><td>Départemental archives</td><td>325</td><td>74.88</td><td>33</td><td>36.26</td><td>93</td><td>100.00</td></tr><tr><td>Municipal archives</td><td>44</td><td>10.14</td><td>0</td><td>0.00</td><td></td><td></td></tr><tr><td>Other archival services</td><td>6</td><td>1.38</td><td>17</td><td>18.68</td><td></td><td></td></tr><tr><td>Archival sources</td><td>434</td><td>100.00</td><td>91</td><td>100.00</td><td>93</td><td>100.00</td></tr><tr><td colspan="7"><strong>Archival series</strong></td></tr><tr><td>AN-G7 General control of finances</td><td>20</td><td>5.21</td><td>7</td><td>9.46</td><td></td><td></td></tr><tr><td>AN-Z1A Court of Aids</td><td>27</td><td>7.03</td><td>18</td><td>24.32</td><td></td><td></td></tr><tr><td>AD-B Courts and jurisdictions</td><td>285</td><td>74.22</td><td>22</td><td>29.73</td><td>86</td><td>92.47</td></tr><tr><td>AD-C Provincial administrations</td><td>24</td><td>6.25</td><td>11</td><td>14.86</td><td>7</td><td>7.53</td></tr><tr><td>Other archival series</td><td>28</td><td>7.29</td><td>16</td><td>21.62</td><td></td><td></td></tr><tr><td>Nat. and dép. archival sources</td><td>384</td><td>100.00</td><td>74</td><td>100.00</td><td>93</td><td>100.00</td></tr></tbody></table>

Notes. This table reports the distribution of rebellions and their sources in the Jean Nicolas and Brice Évain surveys across two départements of Brittany.

Consistent with previous analyses, each of these measures is strongly correlated with the share of parishes that experienced at least one recorded

<footnote n="104">¹⁰⁴ I exclude the share of rebellion records citing national archival sources to avoid collinearity with the first two measures. Moreover, I focus on départemental archival sources rather than on broader local sources because municipal sources could generate a spatial bias toward specific localities within départements.</footnote>
rebellion between 1661 and 1789. In other words, these measures help predict the incidence of recorded rebellions at the département level despite being unrelated to the underlying historical data generating process of rebellions.<fnref n="105" />

Specifically, Table 5 presents results from a series of linear regressions. In Column 1, the estimate is statistically significant at the one-percent level and implies that a 10 percent increase in the share of rebellions with départemental archival sources is associated with a 1.3 percent increase in the share of parishes with at least one recorded rebellion.<fnref n="106" /> This single variable accounts for 16 percent of the variation in the outcome. Next, Column 2 shows that the share of rebellions with bibliographic sources is negatively correlated with the incidence of rebellions, though it explains only 6 percent of its variation. Finally, Column 3 indicates a positive correlation between the presence of a local collaborator and the incidence of rebellions, explaining 10 percent of its variation. Including all three measures simultaneously in Column 4 does not change the magnitude of these results, although the coefficient for bibliographic sources is no longer statistically significant. Together, these measures explain 25 percent of the variation in the incidence of rebellions. Of course, the number of parishes with recorded rebellions in a département should also be a function of its population and number of parishes. Indeed, estimates in Column 5 imply that these characteristics explain one-third of the incidence of rebellions. Nevertheless, even when controlling for these factors in Column 6, methodological biases remain significant predictors of the incidence of rebellions recorded in the Jean Nicolas survey.

Based on these findings, I construct a département-level grading scheme to summarize the quality of rebellion records in the Jean Nicolas database. I develop three candidate grading schemes: the first relies exclusively on the measure with the strongest predictive power, i.e., the share of rebellions citing at least one départemental archival source; the second standardizes and aggregates all three measures linearly; and the third aggregates them using weights proportional to their relative predictive powers.<fnref n="107" /> Grades

<footnote n="105">¹⁰⁵ Results are similar when using the log number of rebellions as the outcome variable (see Appendix Table A52). Again, it is important to note that this analysis assumes away biases stemming from the destruction, gaps, and reliability of archival sources.</footnote>

<footnote n="106">¹⁰⁶ Because archival sources for the Île-de-France region are generally located in Paris, I group its eight départements: Paris (78), Seine-et-Marne (77), Yvelines (78), Essonne (91), Hauts-de-Seine (92), Seine-Saint-Denis (93), Val-de-Marne (94), and Val-d'Oise (95).</footnote>

<footnote n="107">¹⁰⁷ Specifically, weights correspond to each measure's associated R-squared from bivariate regressions with the outcome variable (see Columns 1–3 in Table 5), scaled by the total R-squared sum (0.158 + 0.057 + 0.103 = 0.318). The resulting</footnote>
ranging from A to D are then assigned based on the interquartile distribution of each index, with A indicating the highest quality and D, the lowest.

<table><caption>Table 5 – Incidence of Rebellions and Département-Level Biases.</caption><thead><tr><th></th><th colspan="6">Outcome: Share of parishes with at least one rebellion</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Share of rebellions with<br>départemental sources</td><td>0.130***<br>[0.033]</td><td></td><td></td><td>0.106***<br>[0.034]</td><td></td><td>0.060**<br>[0.030]</td></tr><tr><td>Share of rebellions with<br>bibliographic sources</td><td></td><td>-0.119**<br>[0.057]</td><td></td><td>-0.080<br>[0.051]</td><td></td><td>-0.139***<br>[0.039]</td></tr><tr><td>At least one author<br>in département</td><td></td><td></td><td>0.054***<br>[0.018]</td><td>0.042**<br>[0.016]</td><td></td><td>0.039***<br>[0.013]</td></tr><tr><td>Log population in 1793</td><td></td><td></td><td></td><td></td><td>0.076***<br>[0.023]</td><td>0.068***<br>[0.017]</td></tr><tr><td>Log number of parishes</td><td></td><td></td><td></td><td></td><td></td><td>-0.126***<br>[0.023]</td></tr><tr><td>Départements</td><td>88</td><td>88</td><td>88</td><td>88</td><td>88</td><td>88</td></tr><tr><td>R-squared</td><td>0.158</td><td>0.057</td><td>0.103</td><td>0.249</td><td>0.336</td><td>0.546</td></tr></tbody></table>

*Summary statistics.* Share of parishes with at least one rebellion: 0.124 (mean), 0.085 (s. d.). Share of rebellions with départemental sources: 0.349 (mean), 0.260 (s. d.). Share of rebellions with bibliographic sources: 0.255 (mean), 0.172 (s. d.). At least one author in département: 0.477 (mean), 0.502 (s. d.).

*Notes.* This table reports OLS coefficients. The unit of observation is a département. The eight départements of the Île-de-France region are grouped together. Shares are between 0 and 1. Robust standard errors are reported in brackets.

*Statistical significance.* ***p ≤ 0.01. **p ≤ 0.05. *p ≤ 0.10.

I then evaluate the predictive power of these grading schemes through fixed-effects regressions. The results in Columns 1–3 of Table 6 indicate that départements assigned with higher quality grades—regardless of the grading scheme—exhibit a greater share of parishes with recorded rebellions. The third grading scheme—based on a weighted aggregation of the three measures—demonstrates the highest predictive power. Controlling for département population and number of parishes in Columns 4–6 does not substantively alter these results. Therefore, I adopt the third grading scheme, which I match with the *nicolas_events* dataset. Overall, about one third of records have the grade of A (34 percent), another third, the grade of B (34 percent), and the rest, the grades of C (18 percent) and D (14 percent).<fnref n="108" /> Users of the Jean Nicolas database

weights are 50 percent for the share of rebellions citing départemental archival sources, 18 percent for bibliographic sources, and 32 percent for the presence of a collaborator.

<footnote n="108">¹⁰⁸ Appendix Table A54 provides the statistical distribution of this grading scheme, and Appendix Figure A26, its spatial distribution.</footnote>
should contrast their results across rebellion records characterized by different quality grades.

<table><caption>Table 6 – Incidence of Rebellions and Département-Level Quality Grade.</caption><thead><tr><th colspan="7">Outcome: Share of parishes with at least one rebellion</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td>Quality grade</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>A</td><td>0.078***<br>[0.026]</td><td>0.059**<br>[0.028]</td><td>0.098***<br>[0.024]</td><td>0.056***<br>[0.019]</td><td>0.029<br>[0.020]</td><td>0.065***<br>[0.015]</td></tr><tr><td>B</td><td>0.035<br>[0.024]</td><td>0.034<br>[0.022]</td><td>0.062***<br>[0.022]</td><td>-0.011<br>[0.020]</td><td>0.011<br>[0.019]</td><td>0.038**<br>[0.019]</td></tr><tr><td>C</td><td>0.002<br>[0.022]</td><td>0.024<br>[0.023]</td><td>0.035*<br>[0.018]</td><td>-0.021<br>[0.019]</td><td>-0.006<br>[0.021]</td><td>-0.009<br>[0.017]</td></tr><tr><td>D = excluded</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Log population in 1793</td><td></td><td></td><td></td><td>0.088***<br>[0.022]</td><td>0.078***<br>[0.024]</td><td>0.075***<br>[0.021]</td></tr><tr><td>Log number of parishes</td><td></td><td></td><td></td><td>-0.130***<br>[0.021]</td><td>-0.123***<br>[0.022]</td><td>-0.122***<br>[0.022]</td></tr><tr><td>Grade type</td><td>AD</td><td>Flat</td><td>Weighted</td><td>AD</td><td>Flat</td><td>Weighted</td></tr><tr><td>Départements</td><td>88</td><td>88</td><td>88</td><td>88</td><td>88</td><td>88</td></tr><tr><td>R-squared</td><td>0.139</td><td>0.062</td><td>0.182</td><td>0.459</td><td>0.360</td><td>0.461</td></tr></tbody></table>

*Summary statistics.* Share of parishes with at least one rebellion: 0.124 (mean), 0.085 (s. d.).

*Notes.* This table reports OLS coefficients. The unit of observation is a département. The eight départements of the Île-de-France region are grouped together. Shares are between 0 and 1. *Quality grade* refers to the grade based on the measure of availability of départemental archival sources; *Flat*, to the grade based on the flat aggregation of all three measures; and *Weighted*, to the grade based on the weighted aggregation of all three measures. Robust standard errors are reported in brackets.

*Statistical significance.* ***p* ≤ 0.01. **p* ≤ 0.05. *p* ≤ 0.10.

## 5. GUIDELINES FOR A PROPER USE OF THE JEAN NICOLAS DATABASE

In summary, I propose a set of practical guidelines to help ensure that analyses based on the Jean Nicolas database yield robust and credible results:

1. **Typology.** Carefully consider the typology of events included in the analysis, as some may fall outside the scope of political unrest (see Section 2.2.2).

2. **Coverage.** Evaluate the representativeness of the analysis sample when using variables with limited coverage (see Sections 3.1.4–3.1.7).

3. **Sources.**
(a) **Archival and bibliographic sources.** Test the robustness of analytical result to excluding rebellion records based exclusively on bibliographic sources (see Section 4.2.1).

(b) **National and local sources.** Contrast analytical results across rebellion records that draw on national versus local archival sources (see Sections 4.2.1 and 4.2.3).

(c) **Archival series and recording actors.** Check that analytical results are not overly influenced by any single archival series representing a specific recording actor (see Section 4.2.1).

4. Authorship.

(a) **Jean Nicolas and his collaborators.** Examine whether analytical results change depending on whether rebellion records were authored by Jean Nicolas or his collaborators (see Section 4.2.2).

(b) **Regional stratification of the survey.** Leverage within-département variation by using département-level fixed effects (see Section 4.2.2).

5. **Quality grades.** Contrast analytical results across rebellion records with different quality grades (see Section 4.2.4).

6. DATA AVAILABILITY

The content of the Jean Nicolas database is distributed through the Harvard Dataverse under the CC-BY 4.0 license at https://doi.org/10.7910/DVN/ANQXMQ (Gay, 2025). The file organization of the database is provided in Figure 10. It contains five sets of files: the 8,977 original records of the Jean Nicolas survey in PDF format (nicolas_records), a copy of Jean Nicolas's logbook in PDF format (nicolas_logbook), the events dataset (nicolas_events), the sources dataset (nicolas.sources), and the authors dataset (nicolas_authors).<fnref n="109" /> These three datasets are provided in Stata DTA format as well as in CSV format, with and without value labels. I also provide codebooks in TXT format that contain the list of variables along with

<footnote n="109">¹⁰⁹ The events dataset is also provided for all records of the Jean Nicolas survey under the nicolas_events_all folder.</footnote>
their labels and value labels. All the data and codebook files are available
both in English and in French.<fnref n="110" />

<figure><img src="image_12.png" /><figcaption>Figure 10 – *The Jean Nicolas Database Repository*.</figcaption></figure>

Notes. This figure displays the file organization of the Jean Nicolas database repository (Gay, 2025) available on the Harvard Dataverse at https://doi.org/10.7910/DVN/ANQXMQ.

7. POTENTIAL USES

The Jean Nicolas database offers a wide range of applications. Most
notably, it provides a foundation for analyzing the spatial and temporal
dynamics of popular uprisings in the decades leading up to the French
Revolution (Aubert, 2015). It can also serve as a valuable entry point for
regional studies of social conflict in early modern France (e.g., Évain,

<footnote n="110">¹¹⁰ Datasets and codebooks in French have the extension _FR in their file names. Note that while the labels and value labels are translated, I keep the original variable name to ensure interoperability between datasets.</footnote>
2022).<fnref n="111" /> More broadly, the Jean Nicolas database is of primary interest to scholars in historical political economy seeking to understand the roots of rebellion during this period (Jenkins & Rubin, 2024). Indeed, the HiSCoD version of the Jean Nicolas survey has already been widely used to examine factors underlying popular uprisings in early modern France, including adverse weather conditions (Chambru, 2019), ruling by local elites (Degrave, 2023), French combatants’ exposure to the American Revolution (Jha & Wilkinson, 2023; Ottinger & Rosenberger, 2023), and taxation (Davoine et al., 2025; Giommoni et al., 2025).<fnref n="112" /> Additionally, I have drawn on the Jean Nicolas database to investigate how the state’s growing informational capacity shaped the dynamics of rebellion in the run-up to the Revolution (Albertus & Gay, 2025). Thanks to its fine-grained content, the Jean Nicolas database will contribute to improving our understanding of the roots of popular uprisings in early modern France.<fnref n="113" />

## 8. ACKNOWLEDGMENTS

This article is dedicated to the memory of Jean Nicolas (1928–2025), whose pioneering work made it possible. I am grateful to Michael Albertus, Gauthier Aubert, Pascal Bastien, Nicole Charley, Jamie Folsom, François Godicheau, Dominique Godineau, Sébastien Poublanc, Estefania Santacreu-Vasut for their input on this project. I am especially indebted to Renan Donnerh, Brice Évain, and Philippe Hamon for their invaluable contributions to this long-standing endeavor. I am also thankful to Loris Cuenot, Annie Dago, and Louis Vitrand for their outstanding research assistance. Finally, I thank Cédric Chambru for his valuable input about the construction of the HiSCoD database. I gratefully acknowledge the financial support of the Agence Nationale de la Recherche (ANR) under grants ANR-17-EURE-0010 (Investissements d'Avenir program) and ANR-20-CE38-0015 (ObARDI).

<footnote n="111">¹¹¹ The availability of Jean Nicolas’s logbook will also contribute to a history of this collective survey (Guirault, 2019).</footnote>

<footnote n="112">¹¹² It has also been used to construct control variables for various empirical analyses (Chambru et al., 2024; Degrave et al., 2024; López Peceño, 2024).</footnote>

<footnote n="113">¹¹³ The Jean Nicolas database is not intended to be expanded with contributions from contemporary researchers, primarily because the broad conceptual framework used by Jean Nicolas may blur the boundaries between political unrest and more ambiguous phenomena, such as ordinary criminal acts. Researchers wishing to contribute to a dynamic and evolving database are encouraged to turn instead to HiSCoD, which actively welcomes such contributions—see https://mrsh.unicaen.fr/hiscod/contribuer.html.</footnote>
## 9. CREDIT AUTHORSHIP CONTRIBUTION STATEMENT

**Victor Gay**: Writing – review & editing; Writing – original draft; Visualization; Validation; Supervision; Software; Resources; Project administration; Methodology; Investigation; Funding acquisition; Formal analysis; Data curation; Conceptualization.

## 10. DECLARATION OF CONFLICTING INTERESTS

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

## 11. BIBLIOGRAPHY

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