dataesr/scientific-paragraphs-categorization huggingface dataset:
An online forum discussion on the [WoMoz] mailing list was instigated to understand how such gendered language is perceived by female developers. Unlike proprietary software development, problem-solving in FLOSS development is transparent. A formal (and sometimes also informal) record of the problem-solving process is kept, archived and, mostly, publicly accessible. For instance, most FLOSS projects make use of bug tracking systems to keep a record of problems identified and features requested with respect to their projects and of the efforts that have been made to resolve them. As we already indicated, the process of identifying, reporting, discussing and resolving of problems resembles a process of bricolage, and we study the communication and logs on the Bugzilla bug tracking system to investigate the gender politics embedded in this process.
g. , teamworking, networking and bricolage), but on the other hand, the prevailing 'brogramming culture' leads to undesirable 'gendered arrangements of values [that] perpetuate dominance even in cases where no intimidation is intended  ' Herring 1996. , p. 137). How can we inject the findings from our study back to the apparatuses of computer ethics? Our work contextualizes bricolage in a male-dominated decentralized online work environment such as the FLOSS communities. It bears a lesson for IT managers: the kind of bricolage observed in the FLOSS development is a useful skill and practice, but on the other hand, gender should be strengthened as an important area in computer ethics education to eliminate brogramming culture. Whilst computer ethics has been developed into an academic and practical discipline, we need more rigorous methods to integrate feminist ethics and gender-sensitive languages into computer ethics education  (Adam, 2000; Adam & Ofori-Amanfo, 2000).
To our delight, the city's data and planning framework were structured in such a way that they did not only allow our categorization, but legitimized its wideness. The MOSS (Metropolitan Open Space System) 1 , an integrated municipal framework that oversees all open spaces (i. e. non-built spaces), considers the categories a single system to be managed as such. Mapping them reveals a city in which 75% of the metropolitan area comprises non-built spaces  (Ninot and Tallet 2014). Often made invisible by Table Mountain's looming presence, most of these spaces are unremarkable, forming, with brownfields, a marquetry of discrete urban elements (Figure  3 ). 16 However, while planning sources allowed us to assess the size and location of vacant land, they are insufficient to document the way they are actually used.
The authors wish to thank two  Agence Nationale de la Recherche projects  (project  PERISUD  No. Suds-07-046  headed by  Jean-Louis Chaléard ; project  MEDIAGEO  No. ANR-09-BLAN-0351-01  headed by  Isabelle Lefort ), the  Institut Universitaire de France  and the  DALVAA  project (funded by  Ville de Paris -Émergence , and headed by  Marianne Morange  and  Amandine Spire)  for funding. Jean-François Perrat-Mabillon , and  Florence Padovani  kindly agreed to allow us to use some of their photos.
The voucher enables these individuals to obtain the vaccine free of charge at the pharmacy, without a doctor's prescription. They must then make an appointment with either a doctor or a nurse for the vaccine administration. People in the target groups not identified in the NHIF databases (i. e. persons in a risk group but who do not have LTI status) can obtain a voucher from their doctor but this makes their pathway to vaccination more complex as it requires first a doctor's appointment to get a voucher for free vaccine, then going to the pharmacy for delivery, and then a second appointment for the actual vaccine injection. Despite programmes to provide vaccination access, few countries have reached the objective of 75% uptake of the at-risk groups; Northern Ireland being an exception  [1].
Study design and data source The study consisted of repeated cross-sectional assessments of SIVU in a dynamic cohort: the Permanent Sample of Beneficiaries (Echantillon Généraliste des Bénéficiaires, EGB). It was set up in 2005, by a national random sampling of one of every 97 persons affiliated with one of the three major national health insurance funds in France (salaried workers, agricultural workers and farmers, and self-employed workers)  [11]. The sample is permanent, representative and open: every 3 months, new entrants (e. g. registered births) are added to the database; inversely, personal data of those considered to have exited (e. g. died) are nevertheless preserved in the database to permit their characterisation in longitudinal studies. At the moment of data extraction (August 2017), the EGB included 804,089 beneficiaries.
Data are updated monthly from the NHIF administrative databases and include age, sex, area of residence, insurance fund, reimbursement claims for laboratory tests performed or drugs purchased in the community (classified by Anatomical Therapeutic Chemical (ATC) codes) and status for LTI  [12]. On request of their doctors, LTI status is granted to beneficiaries with longterm and costly diseases and this status exempts them from co-payments for any medical care associated with the disease(s) in question, regardless of their income level  [11]. Since 2006, data regarding the diagnoses associated with admissions to a French public or private hospital, excluding military and psychiatric hospitals, are also available for all individuals in the EGB. For this study, we extracted data for salaried workers and their covered family members (i.
e. the children and non-working spouses of salaried workers) only (ca 86% of the French population), because people benefiting from other insurance funds were not included in the EGB until 2011. Access to the EGB is regulated by law and authorised by the National Committee for Informatics and Privacy (Commission Nationale de l'Informatique et des Libertés), and data are anonymous. We obtained authorisation to access the EGB database from the French NHIF.
Trends in French seasonal influenza vaccination uptake among different target groups For each season n/n + 1, we estimated SIVU rates as the ratio of individuals with a recorded SIV delivery (ATC codes J07BB02, J07BB03, J07CA, excluding A(H1N1) pandemic vaccines) between 1 September of year n and 31 March of year n + 1 to the number of individuals in the corresponding group identified in the database in year n. Each SIV delivered in a community pharmacy is recorded in the NHIF database, including those delivered with a free voucher. To describe the trends of SIVU rates, we standardised directly by age and sex, using the 2007 mainland France national census as the reference, to take into account population ageing and the varying age and sex distributions across target groups.
Study limitations and strengths Vaccinations that took place during occupational medicine visits, vaccination centres or nursing homes, which buy the vaccines for their residents are not reported to the health-related administrative databases of the French NHIF; this resulted in underestimating the coverage rate. However, these limitations are unlikely to affect the trend analysis substantially as the vast majority of vaccinations in France, for all vaccines and all ages, are administered through the private sector, and there is no reason to believe that the small proportion of vaccination delivered outside the private sector has varied over the study period. A strength of our study is that vaccine delivery data are more reliable than self-reported vaccination behaviour in surveys  [20]. Indeed, although delivery of the vaccine at the pharmacy does not always convert into actual vaccination, the proportion of at-risk individuals making a successful effort to obtain the vaccine and not using it is likely to be low  [9].
The thresholds and the correlation coefficient between Y 1 and Y 2 are estimated using the maximum likelihood (ML) technique  [31]. The statistical software R includes a dedicated library named polychor to estimate this correlation coefficient perform using the ML method. However, depending on the purpose, an estimate of this correlation coefficient can be sufficient and is obtained from the contingency table  [32] : ρ ≃ cos π 1 þ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi ðN 1 N 4 Þ=ðN 2 N 3 Þ p ; ð7Þ where N 1 , N 2 , N 3 , and N 4 are the components of the contingency table (cf. Table  I ). Their sum is equal to the total number of students: N 1 þ N 2 þ N 3 þ N 4 ¼ N.
IX. APPLICATION TO PEER INSTRUCTION Let us consider a practical application case of an introductory mechanics course taught in a French École d'Ingénieurs from January 2016 to April 2016. This course was composed of ten lectures using Peer Instruction followed by tutorials in small groups. During lectures, all 190 students had a personal clicker. On average, 3. 7 full Peer Instruction processes (first individual vote, peer discussion, and second individual vote) were performed during a lecture, leading to a database of 37 pre-and postdiscussion scores to the ConcepTests. Because of a participation rate at each vote around 80%, the average number of students answering twice to a ConcepTests is 125 (with a standard deviation of 24). Results of votes are plotted in Fig. 4. For each ConcepTests, the effect size is estimated from the preand postdiscussion scores using Eq.
6. Values of the correlation coefficient using Eq. (  7 ) as a function of its value using the maximum likelihood method. FIG. 7. Effect size as a function of the correlation coefficient estimated using Eq. (  7 ) for the 37 ConcepTests. Horizontal lines correspond to values for small (0. 2), medium (0. 5), large (0. 8), and very large (1. 2) effect sizes. The vertical line corresponds to ρ ¼ 0. 3. variables  [31]. Hence it can be directly used with data using an R or Python library. However, assumptions behind this correlation coefficient are only in agreement with the GRM and not the PCM. Hence we recommend for the purpose of the study to use, preferentially, the GRM to calculate the effect size.
Morphometric analysis of affinity and sex attribution Classical cranial measurements defined by Martin  [67]  or Bra ¨uer  [68]  were acquired on the Zlaty ´kůň reconstructed cranium and analysed in comparison with recent and Upper Palaeolithic European specimens. Three European populations (Austrian, Hungarian and Norse) from the Howells craniometric database (https://web. utk. edu/~auerbach/HOWL. htm)  [69, 70]  were used to represent recent variability of modern humans. Cranial metric data were collected from the published literature on 68 reliably dated UP specimens (for references see S3 Table ). Because fossils were often sexed by assessing the skull or the overall robusticity of the skeleton, attention was paid to how their sex was assessed. Information on the sex of individuals was used if it was determined by primary diagnosis from the pelvis  [71, 72] , secondary diagnosis following reliable criteria (see  [15, 73] ) or genetic analysis.
Otherwise, the sex was considered unknown. In total, 20 cranial measurements were inspected (see Results for definitions). From the set of cranial variables, 13 were comparable with variables in the Howells database. Because of the differential taphonomic preservation of the comparative specimens, missing data were imputed using the PCA algorithm, which takes into account similarity between individuals and relationships between variables  [74]. On the basis of multiple imputations, we removed specimens for which the presence of missing values caused too much uncertainty about their position along the first two principal axes. This treatment is consistent with the study of Arbour and Brown  [75] , which concludes that the estimation of missing data provides a better image of reality when only the most uncertain specimens are excluded.
Software The software TIVMI (http://projets. pacea. u-bordeaux. fr/TIVMI) [79]  was used to segment surface models from CT scans and to measure linear dimensions on the Zlaty ´kůň cranium. Surface models were reconstructed from CT scans using the HMH algorithm implemented in TIVMI  [80, 81]. Landmarks and curve and surface semilandmarks were digitized in Viewbox 4 (dHAL software, Athens, Greece). Semilandmarks were placed semi-automatically using a predefined cranial template. Homologous position of semilandmarks was ensured by a sliding procedure. For more details about sliding semilandmarks in three dimensions see  [82]. Missing point estimation, warping and mesh alignment were done using the R package Morpho  [83]. Surface model processing was done in Meshlab (Visual Computing Lab, Italian National Research Council) and Avizo 7.
Analysis of morphological affinity Cranial measurements were taken on the reconstruction of the Zlaty ´kůň cranium to analyse the morphological affinity of the skull (Table  3 , S4 Table ). To filter out the effect of general size, morphological variation was inspected using LDA on log-shape ratios derived from 13 cranial measurements (see Table  4 ) corresponding to measurements in the Howells database. Four discriminant functions were obtained, but only the first two were important for our study. The first discriminant axis separated past UP populations from the recent European populations (Fig  8 ). The second discriminant axis separated the pre-LGM and post-LGM samples. The coefficients of the discriminant functions revealed that the first function differentiated maximum cranial length, maximum cranial breadth, orbital breadth, bi-zygomatic breadth and orbital height.
Acknowledgments We thank the curator of the  National Museum in Prague, Vı ´te ˇzslav Kuz ˇelka , for access to the Zlaty ´kůň fossil. We are grateful to the following institutions, curators and researchers that provided Mathilde Samsel access to their facilities and granted her permission to examine the palaeoanthropological material in their care:  Institut de Paleontologie Humaine  ( H. de Lumley ,  A. Vialet ),  Musee d'Archeologie Nationale (C. Schwab) ,  Musee d'art et d'archeologie du Perigord (V. Merlin-Anglade) ,  Musee d'Histoire Naturelle Victor Brun à Montauban, Museo Geologico "G. G. Gemmellaro" di Palermo (C. di Patti) ,  Musee Labenche de la Ville de Brive (L. Michelin) ,  Musee National de Prehistoire  (J. -J. -Cleyet-Merle), SRA Rhone Alpes & Musat à Saint-Paul-Trois-Chateaux (M.
Explanatory variables Three main types of questionnaires (for households, for mothers, and for children) were designed to record the data on any indicators of household socioeconomic and socio-demographic status, household food security, and care practices for children and their mothers. The Household Food Insecurity Access Scale (HFIAS) was used to determine the household food insecurity including all nine generic questions that require recollection about the worry of food availability and accessibility in the previous months  [21, 22]. The responses were summed to create a total score between 0 (the most food secure household) and 27 (the most food insecure household), which was determined using the Household Food Insecurity Access Prevalence (HFIAP) status indicator as a proxy of the household food insecurity prevalence  [21].
Statistical analyses Data were recorded using the Epi-Data® version 3. 1 software and subjected to statistical analysis using the Stata® 11. 1 software. Statistical procedures were adapted to the sampling methods (multi-stage random sampling with clusters being the primary sampling unit). For each participant included in the study, a weighting of the inverse multiple stage probability of being selected in the study was computed and the survey data analyses procedures of the Stata software were used. Descriptive statistics were computed and the results were presented as means (95% confidence intervals) or medians (25th-75th percentiles) for the quantitative variables or as percentages for the qualitative variables. Comparison between the means or percentages was performed using a Student's t-test or a chi-squared test, taking into account the complex sampling frame.
A memory recall bias cannot be ruled out, for example, with regard to the child's history of illness and breastfeeding behavior. Data were not collected on parasitic infections, birth weight, and daily caloric intake. These variables are potential confounders and their absence can lead to an erroneous interpretation of our results. A parasitic infestation can have an impact on the child's nutrition and growth, altering the intestinal absorption of fats and nutrients  [1, 36]. Moreover, information on the child's birth weight, which is strongly associated with the child's size, was not taken into account due to the high number of missing values. The exact daily caloric intake was not ascertained. Household wealth was assessed using indirect measures (household amenities and asset ownership) due to the inability to collect accurate information on household income and expenditure, which are better measures of household wealth.
In addition, the proliferation of websites offering customer reviews and wealth of reviews available may disorient consumers attempting to evaluate the quality and performance of services before purchase. More third-party e-tailers are attempting to convey to customers relevant information and signals that help them to understand and evaluate the quality and performance of products sold online  [42]. These signals are, for example, the number of "helpful votes" provided by the users of a website that highlight the reviews they read and value as helpful. Research has shown that helpful OCRs increase the sales of etailers  [6, 30]. Existing research on eWOM has mainly focused on attempting to understand the determinants of review helpfulness. To assess review helpfulness, existing studies mostly draw upon the evaluation of the observation of textual details from databases of reviews obtained from websites such as Amazon, which use voting mechanisms asking readers about the extent to which an OCR was helpful [e.
g. , 1, 4,  23, 38, 45, 52, 54, 59, 62]. However, it has been suggested that helpful voting mechanisms can be easily manipulated  [59] , and a large proportion of reviews, particularly more recent ones, have few or no helpfulness votes  [11]. In addition, previous studies using large datasets have had inconsistent conclusions on the determinants of review helpfulness  [38]. Moreover, previous research efforts have not analyzed consumers' perception of information helpfulness (IH). Third-party e-tailers that sell services (i. e. , Booking. com) provide several types of information to help consumers assess the quality of services including recommendation signals and popularity signals (i. e. , number of reviews per service), which, in parallel with review messages, may help customers to diagnose the quality and performance of the services sold by these organizations.
Previous studies have not measured the role that the above-mentioned typologies of information play on consumers' perceived IH. In our study, we use perception measures because existing studies that used datasets from Amazon and similar websites, although useful, mainly investigated the "visible" aspects of review helpfulness and focused on single reviews. However, some other factors such as perceived source homophily or perceived source expertise and trustworthiness or the helpfulness of recommendation and popularity signals cannot be measured through quantitative textual analysis  [27]. We believe that these factors provide a more holistic understanding that helps explain perceived IH. To fill this gap, in this study, we measure the determinants of perceived IH of services (i. e. , tourism services) from the consumer's perspective.
The second important concept in this study is IH. Information in a social commerce platform is deemed to be helpful if it provides information that is perceived by consumers to be helpful to become familiar with, understand, and evaluate the quality and performance of a product sold online  [42]. In the eWOM literature, scholars have recently focused their attention on the determinants of helpful votes to a review. Table  1  summarizes the relevant literature on review helpfulness, illustrating that most existing studies analyze consumer reviews for goods posted on e-tailer's websites such as Amazon. com, and that have created large datasets and used the review's "helpful votes" that a review receives to measure review helpfulness  [1, 4, 23, 38, 45, 52, 54, 59, 62]. There is a dearth of studies that, from a consumer's perspective, analyze more holistically the determinants of IH in third-party e-tailers.
Informational influences Two-sided reviews Two-sided information refers to a (review) message that discusses both the positive and the negative sides of a service  [43] , which is in contrast to one-sided information that only presents positive (or negative) aspects of a product/service  [13]. Previous studies that have focused on review text characteristics adopted datasets of customer reviews from e-tailers, measuring review length, readability, and linguistic correctness  [4, 16, 30, 38, 52, 54, 59, 62]. However, services evaluation is often subjective and due to the high level of emotions embedded in the evaluation of services. Thus, it may be more important for a consumer to access consumer reviews that are balanced and are relevant for understanding whether a particular service is able to satisfy his/her particular needs  [26].
Data collection The data collection was carried in Hong Kong (HK), which was selected as the country base for this study because Internet penetration is very high. Data were collected at the HK International Airport by asking travelers in the waiting areas who have had recent experiences using OCRs when booking accommodation and restaurants to complete an online questionnaire using an iPad provided by one of the researchers of this study. Data were collected using an online questionnaire created using professional survey design software (Survey Monkey) that was primarily composed of closed-ended questions that were measured using a 7-point Likert scale ranging from strongly disagree (1) to strongly agree  (7). The questionnaire was available both in English and in Cantonese. The backward translation method was used.
The questionnaire was first available in English and was translated into Cantonese by a professional with a bilingual (English and Cantonese) language proficiency. A second Cantonese native speaker translated back the Cantonese version into English. No differences emerged between these two versions. For the main study, during a period of two months, a total of 611 responses were collected. However, 41 questionnaires were excluded because they were not completed properly, which yielded a total of 570 usable questionnaires. No incentive was associated with the data collection technique adopted in this study.
85, the most conservative threshold for establishing discriminant validity  [36, 79]. According to Henseler et al. [36] , for conceptually similar constructs, HTMTinference criterion can be used, which suggest that the value of HTMT ratio of correlation should be lower than 1. The value between the two conceptually similar constructs of source expertise and source trustworthiness in our study is 0. 938, and thus it is acceptable. The above test results suggest that discriminant validity of the constructs can be confirmed. In this study, all the data for all exogenous variables were collected through using a survey. This requires testing for the potential presence of common method variance (CMV) among these variables. The questionnaire did include a construct (marker variable) that was theoretically unrelated to indicators in the model.