cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.4ugx4f
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Crucianella divaricata Korovin"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010847-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cg3btr
title: Occurrence Download

description: A dataset containing 167 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Myriopteris pringlei (Davenp.) Grusz & Windham"
 ]
}

 The dataset includes 167 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001597-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ngzndc
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Crepidium lawleri (Lavarack & B.Gray) Szlach."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012344-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yccstz
title: Occurrence Download

description: A dataset containing 247 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eugenia klaineana (Pierre) Engl."
 ]
}

 The dataset includes 247 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046316-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.re6arc
title: Occurrence Download

description: A dataset containing 392 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Myriopteris wrightii (Hook.) Grusz & Windham"
 ]
}

 The dataset includes 392 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001599-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5ka8v4
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corydalis krasnovii Mikhailova"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010846-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zxdsvh
title: Occurrence Download

description: A dataset containing 91 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eugenia koolauensis O.Deg."
 ]
}

 The dataset includes 91 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046322-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xamyc5
title: Occurrence Download

description: A dataset containing 17696 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Heteroconger longissimus Günther, 1870",
 "HasCoordinate is true"
 ]
}

 The dataset includes 17696 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039961-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/lfcuzj
title: COVID-19 Local and Provincial Government Survey (LPGS)

description: In order to understand the efforts of local governments (LGs) in Nepal to contain and prevent the spread of COVID-19, their ability to coordinate relief measures with other spheres of government, financing capacity and fiscal demands, the design of the COVID-19 response including vaccination rollout as well as challenges faced by LGs, the research team administered three rounds of the Covid-19 Local and Provincial Government Survey (LPGS) to officials and bureaucrats at the municipality level in all seven provinces. The survey is embedded in the Research and Evidence for Nepal’s Transition (RENT) project funded by the Foreign, Commonwealth and Development Office (FCDO) and a joint effort between researchers at Yale University, the London School of Economics, Stanford University and Bocconi University, in collaboration with the Governance Lab and the Nepal Administrative Staff College. For more information about the project and related publications: https://egc.yale.edu/ie/projects/research-and-evidence-nepals-transition.
DOI: 10.60600/yu/lsclzj
title: A 2 Million-Person, Campaign-Wide Field Experiment Shows How Digital Advertising Affects Voter Turnout

description: We present the results of a large, US$8.9 million campaign-wide field experiment, conducted among 2 million moderate- and low-information persuadable voters in five battleground states during the 2020 US presidential election. Treatment group participants were exposed to an 8-month-long advertising programme delivered via social media, designed to persuade people to vote against Donald Trump and for Joe Biden. We found no evidence that the programme increased or decreased turnout on average. We found evidence of differential turnout effects by modelled level of Trump support: the campaign increased voting among Biden leaners by 0.4 percentage points (s.e. = 0.2 pp) and decreased voting among Trump leaners by 0.3 percentage points (s.e. = 0.3 pp) for a difference in conditional average treatment effects of 0.7 points (t1,035,571 = −2.09; P = 0.036; DICˆ=0.7 points; 95% confidence interval = −0.014 to 0). An important but exploratory finding is that the strongest differential effects appear in early voting data, which may inform future work on early campaigning in a post-COVID electoral environment. Our results indicate that differential mobilization effects of even large digital advertising campaigns in presidential elections are likely to be modest.
DOI: 10.60600/yu/wkzmnb
title: On the Merits of Separate Spaces: Why Institutions Isolate Cooperation and Division Tasks

description: Do institutions shape the possibility of sustaining cooperation when the same individuals must first divide resources and then attempt to cooperate? It could be that simply having received an inequitable division undermines cooperative behavior, reducing aggregate welfare. Alternatively, it might be that only when interacting with the same individual or group does this spillover occur, in which case separating tasks across institutions may prevent this negative spillover. To test these arguments, we designed a two-stage incentivized experiment in which participants interact in a division task and then in a task in which cooperation improves aggregate welfare. In two experiments, individuals were randomly assigned to interact either with the same individual for both tasks or with a different individual for each task. In the second experiment, individuals could also interact with a person who was in the same arbitrary group as their partner in the division task. Holding constant both past history and past partner behavior, the results of these experiments provide support for a Partner History effect in which the mechanism that produces spillover is interacting with the same individual in both decisions. We also find evidence for a weaker Group History effect in which negative spillover occurs when the partner in the cooperative task is a member of the same group as the partner from the division task.
DOI: 10.60600/yu/mivsqe
title: Gender Composition Predicts Gender Bias: A Meta-Reanalysis of Hiring Discrimination Audit Experiments

description: Since 1983, over 70 employment audit experiments, carried out in more than 26 countries across five continents have randomized the gender of fictitious applicants to measure the extent of hiring discrimination on the basis of gender. The results are mixed: some studies find discrimination against men and others discrimination against women. We reconcile these heterogeneous findings through a ``meta-reanalysis'' of the average effects of being described as a woman (versus a man), conditional on occupation. We find a strongly positive gender gradient. In (relatively better paying) occupations dominated by men, the effect of being a woman is negative while in the (relatively lower paying) occupations dominated by women, the effect is positive. In this way, heterogeneous employment discrimination on the basis of gender preserves status quo gender distributions and earnings gaps. These patterns hold among both minority and majority status applicants. (2023-03-31)
DOI: 10.60600/yu/bkhfgp
title: What to Expect When You’re Electing: Citizen Forecasts in the 2020 Election

description: Political divisions in the lead-up to the 2020 US presidential election were large, leading many to worry that heighted partisan conflict was so stark that partisans were living in different worlds, divided even in their understanding of basic facts. Moreover, the nationalization of American politics is thought to weaken attention to state political concerns. 2020 therefore provides an excellent, if difficult, test case for the claim that individuals understand their state political environment in a meaningful way. Were individuals able to look beyond national rhetoric and the national environment to understand state-level electoral dynamics? We present new data showing that, in the aggregate, despite partisan differences in electoral expectations, Americans are aware of their state’s likely political outcome, including whether it will be close. At the same time, because forecasting the overall election outcome is more difficult, Electoral College forecasts are much noisier and display persistent partisan difference in expectations that do not differ much with state of residence. (2022-06-24)
DOI: 10.60600/yu/ca4ull
title: Health Risks and Voting: Emphasizing Safety Measures Taken to Prevent COVID-19 Does Not Increase Willingness to Vote in Person

description: The COVID-19 pandemic made salient the risks posed by an infectious disease at a polling place. To what degree did such health risks, as with other changes to voting costs, affect the willingness to vote in person? Could highlighting safety measures reduce the association between COVID fears and unwillingness to vote in person? Using both a representative survey of Connecticut voters and a survey experiment, we examine whether concerns about health diminish willingness to vote in person. We find correlational evidence that those who are more worried about COVID-19 are less likely to report they will vote in person, even when considering risk mitigation efforts. We then present causal evidence that mentioning the safety measures being taken does little to offset the negative effect of priming COVID-19 risk on willingness to vote in person. These results contribute to a growing literature that assesses how health risks affect in person voting.
DOI: 10.60600/yu/rfduqu
title: Evaluating Bias and Noise Induced by the U.S. Census Bureau’s Privacy Protection Methods

description: The U.S. Census Bureau faces a difficult trade-off between the accuracy of Census statistics and the protection of individual information. We conduct an independent evaluation of bias and noise induced by the Bureau’s two main disclosure avoidance systems: the TopDown algorithm used for the 2020 Census and the swapping algorithm implemented for the three previous Censuses. Our evaluation leverages the Noisy Measurement File (NMF) as well as two independent runs of the TopDown algorithm applied to the 2010 decennial Census. We find that the NMF contains too much noise to be directly useful without measurement error modeling, especially for Hispanic and multiracial populations. TopDown’s postprocessing reduces the NMF noise and produces data whose accuracy is similar to that of swapping. While the estimated errors for both TopDown and swapping algorithms are generally no greater than other sources of Census error, they can be relatively substantial for geographies with small total populations.
DOI: 10.60600/yu/7vdieq
title: The Power of Protest in the Media: Examining Portrayals of Climate Activism in UK News

description: Existing research on American climate opinion demonstrates that a wide variety of variables impact whether voters support a given policy. However, little research has empirically tested which variables matter the most in creating durable majority support for climate policies, and how varying outcomes of those variables can impact such support. I use a conjoint experiment to test the extent to which American voters value the six most important variables around climate mitigation policy, as illustrated in the current literature, and which potential options among those values attract the greatest support. I improve in external validity over previous conjoints by introducing partisanship and policy level, as well as more realistic ranges for policy cost. I find that voters generally-and across racial, gender, and partisan lines- value some variables ten times higher than others, and prefer Democratic or Bipartisan policies that are low cost and provide a variety of benefits.
DOI: 10.60600/yu/lpn0ue
title: Bridging the Blue Divide: The Democrats’ New Metro Coalition and the Unexpected Prominence of Redistribution

description: The electoral base of the Democratic Party has been transformed over the past generation. Democrats have lost ground in rural America while adding strength in cities and, more recently, suburbs. A major consequence of this shift has been the creation of a “U-shaped” Democratic voting base, with both poorer metro voters and affluent suburbanites siding with the party. This spatial alliance overlays a multi-racial one, as Democrats rely more heavily on voters of color than any other major party in American history. Many analysts have argued that the Democratic Party has managed this sea change by shifting from economic to cultural and identity appeals. This claim is consistent with leading models of two-dimensional party competition, as well as a fair amount of cross-national research on parties of the left and center-left in contemporary knowledge economies. However, we find little evidence for this claim in national Democrats’ messaging (via party platforms and on Twitter), nor, more important, in their actual policy efforts. Instead, we show that even as Democrats have increasingly relied on affluent, educated voters, the party has embraced a more ambitious economic agenda. The national party has bridged the Blue Divide not by foreswearing redistribution or foregrounding cultural liberalism, but by formulating an increasingly bold economic program—albeit one that elides important inequalities within its metro-based multi-racial coalition. Understanding how and why Democrats have taken this path is central to understanding not just the party’s response to its shifting electorate, but the way parties manage coalitional change more broadly.
DOI: 10.60600/yu/etlp49
title: Chain Novel, or Markov Chain? Estimating the Authority of U.S. Supreme Court Case Law

description: How does the authority of case law evolve over time? On the Dworkinian legal formalist view, cases increase in authority as they become more embedded in the “chain” of legal precedent, but on the Holmesian legal realist view, each case's authority is proportional to its ability to predict future legal outcomes. In this article, I show how modeling the citation network of U.S. Supreme Court case law not as a chain novel (à la Dworkin) but instead as a Markov chain (à la Holmes, or so I argue) unlocks an intuitive measure of case authority—called HolmesRank—that outperforms the existing approach in a variety of validation tasks. I then demonstrate how the authority scores produced using this Markov machinery empower the analysis of two important normative questions: (1) the ideological basis of lasting precedential authority and (2) the causal effect of the Supreme Court's citation choices on lower court compliance.
DOI: 10.60600/yu/ocebtw
title: Seeing the State in Action: Public Preferences About and Judgments of Common Police–Civilian Interactions

description: New technologies allow unprecedented public visibility of routine police–civilian interactions, but we know little about how the public wants the police to behave during them. We examine public evaluations about preferred punishment and fair treatment using vignette experiments that randomize multiple features of police–civilian interactions. These causal estimates reveal that for the mass public, officer race does not affect public attitudes, while participant demeanor, markers of threat, and civilian race do. Police–civilian interactions are evaluated through a lens of reciprocity: Hostile officers are judged as less fair, while hostile and armed civilians are viewed as deserving of harsher punishment. When civilians remain polite and threat is low, there is little support for punitive outcomes, but poor civilian behavior warrants more punitive state action. Moreover, people prefer more punishment for White compared with Black civilians, as well as in interactions with White officers and civilians compared with those in which both parties are Black. Interactions with a White officer and a Black civilian are judged as less fair, as are the fairness of assigned punishments in them. Finally, views about fairness are not equivalent to views about appropriate sanctions. These results provide critical evidence about public attitudes regarding police punishment and fairness in order maintenance.
DOI: 10.60600/yu/p0dnoj
title: Understanding the Policy Features That Affect Indians’ Support for India’s 2070 Net-Zero Goal

description: In 2021, the Indian government announced the goal of net-zero carbon emissions in India by 2070. India’s vulnerability to climate impacts and central role in reducing global emissions make it essential to understand the policy features that affect Indians’ support for the 2070 goal. We conducted a conjoint experiment (N = 1,500) to test Indians’ support for the 2070 goal depending on differences among possible policy features including economic programs, allocation of funds collected via coal taxes, policies to mitigate pollution, who participates in the policy-making process, and adaptation policy. We find that Indians express stronger support for the 2070 goal when it includes jobs programs for Indians who lose their job in a coal-fired power plant, policies to mitigate pollution, investment or redistribution of funds collected via coal taxes, and adaptation policies to protect the most vulnerable Indians and critical infrastructure. Support for certain policy features varies depending on income, education, and caste.
DOI: 10.60600/yu/bqf3yy
title: Targeted Abortion Frames Do Not Mobilize Political Action-Taking

description: With the advent of Big Data, political organizations are increasingly able to target messages by demographic information. Past research has found mixed results whether targeted frames are more effective in persuading participants than standard, broad-based frames. In this paper, we study the efficacy of targeted appeals in mobilizing likely supporters to take action on abortion rights. In a departure from past research, we focus our efforts on mobilization (rather than persuasion) and identity-based appeals (rather than policy preference-based appeals). We first collect real-world evidence through elite interviews that practitioners in the space actually use targeted appeals to garner support. We then partner with a political organization to conduct an online field experiment using targeted frames. Finally, we conduct two survey experiments to test the efficacy of targeted frames in a controlled setting. We find that targeted mobilization appeals are no more effective than standard appeals in mobilizing existing supporters to take action on behalf abortion rights. We do not find evidence of a demobilizing effect when frames are mis-targeted. Our findings suggest that organizations can innovate their messaging to target new groups without alienating core supporters.
DOI: 10.60600/yu/ndp800
title: Everything in Moderation? The Effect of Extremist Nominations on Individual and Corporate PAC Fundraising

description: The author employ a close primaries regression discontinuity design to examine how “as-if random” nominations
of extreme versus moderate House candidates influence general election contributions from individual
donors and corporate political action committees (PACs) from 1980 to 2020.
DOI: 10.60600/yu/z3mq8g
title: Strategic Campaign Attention to Abortion Before and After Dobbs

description: In 2022, the US Supreme Court overturned the constitutional protection of abortion rights established in Roe v. Wade. In doing so, Dobbs v. Jackson Women’s Health Organization moved status quo on abortion policy more into line with the Republican Party’s stance. Subsequent research has documented the decision’s impact on mass political behavior and opinion, yet less is known about its impact on the behavior of political elites. I provide evidence on congressional candidates’ strategic responses to the decision with original data on campaign platforms (N = 4,703) from election cycles before and after Dobbs. After the decision, Democrats became significantly more likely to campaign on abortion and to do so using unambiguous language, while Republicans
increasingly obfuscated their positions on the issue. Pre-post-Dobbs change in partisan divergence in campaign attention to abortion was driven most strongly by candidates in states with abortion bans set to take effect upon overturning of Roe (i.e., trigger laws and/or pre-Roe laws). Importantly, these shifting patterns of campaign attention were not present in other issue domains, consistent with changes in attention to abortion being driven by Dobbs rather than other contemporaneous factors.
DOI: 10.15156/bio/sh0196595.10fu
title: SH0196595.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.