dataesr/scientific-paragraphs-categorization huggingface dataset:
Data Data was collected from December 2015 to May 2016, from a sample of Malaysians ranging from non-managers to senior managers. Public-sector personnel were excluded as they are unlikely to find themselves in acquisition situations. A total of 4,923 personalized e-mail invitations were sent to individuals from over 300 organizations, each with a non-transferable survey weblink. Respondents were recruited from multiple sources: social media sites (LinkedIn and Facebook), professional associations (university alumni groups and chambers of commerce), firms, contact lists, personal connections of the first author, and respondent referrals. To enhance the response rate, respondents were guaranteed complete confidentiality and anonymity, and could elect to receive a summary of our findings. We offered 50 restaurant vouchers worth €250 in total through a prize draw conducted at the end of the study.
Policy capturing experiment We collected data using the policy capturing method (PCM), a field-experimental approach. Management-related papers are increasingly using experiments to examine decision-making  (Aguinis & Bradley, 2014) , including PCM in acquisitions  (Pablo, 1994; Stahl et al. , 2012; Yildiz & Fey, 2016)  and internationalization  (Hitt, Dacin, Levitas, Arregle, & Borza, 2000; Hitt, Ahlstrom, Dacin, Levitas, & Svobodina, 2004; Tong, Reuer, Tyler, & Zhang, 2015). The calls for more experimental methods in international business  (Zellmer-Bruhn et al. , 2016)  and trust research  (Fulmer & Gelfand, 2012)  are also encouraging. PCM combines elements of controlled experiments and traditional surveys to study decision-making at individual and group levels  (Karren & Barringer, 2002).
Dating methods In order to obtain chronological data for the site of Fatandi V, optically stimulated luminescence (OSL) dating was performed. This palaeodosimetric technique takes advantage of the grains of quartz present in sediments, which behave as a sort of stopwatch capable of recording the time elapsed since their last exposure to light  [14]. This event generally corresponds to the deposition of the sedimentary unit in question. At the site of Fatandi V, 12 sediment samples were taken in 2013 and 2014. During night time, samples were taken by scraping the stratigraphic section, taking care to eliminate from the offset the first centimeters of sediment exposed to the daylight. The samples were taken from 5 distinct zones (Fig  2 ). Samples F1 and F2 were situated beneath Concentration 1, at 70 and 30 cm respectively from the current surface of the archaeological layer.
(2009)   [20]. The results were subsequently corrected with respect to the water concentration at the time of data acquisition. The contribution of cosmic radiation to the total dose rate was calculated using the equation established by  Prescott and Hutton (1994)   [21] , of which the primary parameter is the burial depth of the sample. The OSL measurements, necessary for determining the De, were performed using quartz grains (100-140 μm) extracted from the sediments following a series of mechanical and chemical procedures, according to a method presented in  Lebrun et al. (2016)   [22]. All preparatory steps and measurements were performed under a red-orange light with no effect on the OSL signal. Two measurement techniques were employed: the multi-grain analyses were carried out with a Lexsyg Smart Reader  [23]  and the single-grain analyses with a Risø TL/OSL-DA-20 system  [24].
The analysis of the data was performed with the Analyst program v4. 57 [29]. For each aliquot, the selection criteria were applied based on the values of the recycling ratio (within ±10% of the unity) and recovery ratio (< 5% of the natural signal) as well as on the sensitivity of the signal (first test dose signal > 3 x background). The BayLum package was then used for the Bayesian analysis of the luminescence data (S1 File)  [30] [31] [32] [33]. The independence of the De with regards to the conditions of preheating were tested in the multi-grain mode. For each sample, the preheat temperature was varied between 200 and 280˚C for a duration of 10 s. The preheat temperature for the test dose (cutheat) was fixed at 160˚C for 0 second. Some dose recovery tests (DRT) were also performed, in both multi-grain and single-grain mode, so as to test the capacity of the SAR protocol and the parameters chosen here to recover a dose administered in the laboratory (acceptability interval: [0.
The location of the 19 other pieces was recorded with reference to this artefact. The excavations conducted in 2013 and 2014 made it possible to accurately record the stratigraphic position of the artefacts in the areas where the pieces are still buried, or to observe the absence of lithics in certain areas. We have also kept information on the orientation and dip of the artefacts. This data would allow for fabric analysis, only on stratified artefacts in Concentration 2 and northern areas of the site, and refine the interpretation of burial process in Fatandi V  [46, 47]. However, a large number of Concentration 2 lithics were already eroded and the northern excavation area, in particular North square, is small (Figs  4  and 5 ). The value of a detailed fabric analysis for understanding site formation would therefore be currently limited.
The R package "BayLum"  [32, 33]  (see  [30, 31]  for the mathematical models) allows for the modelling of the OSL sediment sample chronology, taking into account We give here the Bayes estimator. In order to facilitate comparisons, the error associated with the Bayes estimator is calculated to 68% from the credibility interval, even though the Bayes estimator is not strictly in the middle of this interval. The samples with an asterix are those processed by Lebrun et al. (2016)  [22]  and mentioned here as a reminder. https://doi. org/10. 1371/journal. pone. 0243129. t004 the chrono-stratigraphical order. In addition, the package appropriately manages the errors by taking into consideration those which are common to multiple samples. The R package "ArchaeoPhases" (S1 File)  [59, 60] , also based on Bayesian models, allows respectively the estimation of time intervals for all samples-here the sedimentary units identified at the site.
This divergence is all the more marked as the distributions become more dispersed (e. g. significant overdispersion). This divergence could simply reflect the deviation between the mean (arithmetic) and the median of the distributions of De  [61]. For what here follows, we base ourselves on the work of Guerin et al. [61] [62] [63]  and of Heydari and Guerin  [64] , suggesting that even-and above all-in the case where the distributions of De are not normal, the baSAR-Normal model is more accurate and more robust than the CAM or the baSAR-LogNormal_M model. Then the ages were calculated from the single-grain data with the baSAR-Normal model by applying the stratigraphic constraints. These are based on the log presented in Fig 2 : F2<F1 (i. e. F2 is younger than F1); F4<F3; F10<F9, F7<F6<F5<F13<F12; F12 is younger than all the samples of U1.
without any stratigraphic constraints are also indicated. The principal effect of applying the stratigraphic constraints is the resolution of the apparent chrono-stratigraphic inversion between F6 and F7. The deposits of the three sedimentary units identified as U1, U2, and U3 would therefore be chronologically associated with the end of MIS2 and the Holocene. The application of the ArchaeoPhases package allows the estimation of intervals at 68% confidence level from 13,400 to 8,200 BCE [15. 4 to 10. 2 ka at 68%, and 16. 9 to 9. 4 ka at 95%] for U1, and from 10,900 to 7,500 BCE [12. 9 to 9. 5 ka at 68%, and 14. 2 to 8. 7 ka at 95%] for U2, which covers the in situ archaeological layer, and from 7,600 to 4,600 BCE [9. 6 to 6. 6 ka at 68%, and 10. 5 to 6. 2 ka at 95%] for U3. The F12 sample coming from the in situ archaeological layer in the northern part of the site gives an age interval of 11,300-9,200 BCE at 68% confidence level [13.
cal BC] in Mali  [8] , within the different Neolithic groups at Tilemsi in the north of Mali from the beginning of the 3 rd millennium BCE [3 rd mill. cal BC]  [90, 91]  or at WindeKoroji from the beginning of the 2 nd millennium BCE [2 nd mill. cal BC], or north of Ounjougou, still in Mali  [92]. On the other hand, further south, in Ghana, a complete cultural ensemble, called Kintampo culture, as seen at Ntereso, is characterized by this same type of bifacial armatures accompanied by ceramics reminiscent of certain features of southern Sahara ceramics, such as those of Kobadi  [93] [94] [95]. The environmental data collected at Ounjougou and Fatandi could in theory suggest environmental factors as an element for distinguishing cultural practices and material industries. Nevertheless, throughout a large part of the Holocene, there is a real juxtaposition of Saharan and sub-Saharan populations with one or another of these kinds of armatures.
Acknowledgments We would like to warmly thank several institutions and individuals for their participation or support of the research program, including: -The Swiss National Science Foundation which, through its long-term support, allows us to achieve the results presented here; -The  French-Swiss "Lead Agency" SNSF-ANR , which provided us with joint research funding for the French and Swiss teams; -The  Switzerland-Liechtenstein Foundation for Archaeological Research Abroad (SLSA) , for its additional funding, without which we could not hire Senegalese and Malian workers; -The Faculty of  Sciences of the University of Geneva  for the AFRI budget line, which is essential for the smooth running of this international program;.
MATERIALS AND METHODS A qualitative interpretivist approach was adopted because this allows the discovery of facts that may not have been foreseen by the researcher  (Ghauri and Gronhaug, 2010; Hennink et al. , 2011). This approach takes into account the fact that individuals assign their own meanings to events and situations, hence, people's accounts need to be studied in depth in order to develop a thorough understanding of the phenomenon under consideration  (Crotty, 1998). Levin et al. (2002)  imply that different ethnic origins may influence discrimination and barriers in qualitatively different ways, hence, their discovery clearly necessitates qualitative research designs. Data were collected via semi-structured interviews, all conducted in English, from two groups: Ten Chinese SIE women and 10 native Caucasian British women in the UK.
ACKNOWLEDGMENTS This work was carried out in the framework of the Labex  MS2T , which was funded by the  French Government , through the program Investments for the future managed by the  National Agency for Research (Reference   ANR-11-IDEX-0004-02 ). MD acknowledges support from the  Belgian F. R. S. -FNRS  of which he is a Research Director. VF acknowledges the support from  Ecole Centrale de Nantes  of which he is Full Professor.
Data Analysis Statistical analysis was performed using the environment for statistical computing and graphics R  [51]. Mosquito abundance was defined as the total number of mosquitoes captured, independently of the species. Species richness (S) or number of species or taxa in the community was determined per habitat type and per season. Two estimators of the 'true' number of species in each site, Chao1 and ACE (Abundance-base Coverage Estimator), were calculated using the command estimate R in the 'vegan' package  [52]. Individual-based rarefaction curves for all sites across seasons were constructed from EstimateS software. PCA (Principal Component Analysis) was performed with the FactoMine R package  [53]  to display the association between mosquito species and habitat types, and mosquito species and seasons.
Acknowledgments: We thank members of  VBID-RUBAE ,  Lontsi Michel ,  Ngnidji Yannick ,  Magatsing Ornella ,  Defo Talom ,  Ouaba José ,  Djojo-Tachegoum Carelle  for their assistance in the field. We are also grateful to villagers who allowed us to conduct this study in their villages, mainly the heads of the  Toutsang, Fonakeukeu and Dschang communities in the Menoua Division.
Methods The PMA2020 FTF survey has exempt status (IRB #00000287, exempt as "public health practice", defined by DHHS regulations 45 CFR 46. 102), as determined by John Hopkins' IRB. Approval was granted in July 2014 by the Comited'ethique pour la recherche en sante (IRB #2014-7-81). Consent was obtained orally. For the phone survey, ethical approval was granted by the IRB at the Johns Hopkins Bloomberg School of Public Health (IRB No. 00007961). The ISSP team submitted a protocol to their ethical committee for the RDD survey (IRB No. 2018-3-036). We used two datasets for this analysis. The first dataset is the Burkina Faso PMA2020 Round 5 (R5) FTF survey, designed to track key family planning indicators under the Family Planning 2020 initiative  [16]. PMA2020 R5 implemented a two-stage stratified cluster design to select a national sample of women of reproductive age in Burkina Faso.
This design starts with a probability proportional to size selection of 83 geographic clusters stratified by urban and rural areas followed by a random selection of about 35 households within each sample cluster. Detailed sampling methods and procedures are available in a previous publication  [17]. PMA2020 R5 Burkina Faso was conducted between November 20, 2017-January 20, 2018 and included a total of 2,811 households (98. 5% response rate) and 3,659 females (97. 8% response rate)  [18]. Data collection was performed by a network of trained female interviewers who conducted FTF interviews with members of selected households and with all eligible females 15-49 years from the selected households. Interviewers recorded responses directly on cell phones and uploaded the data when cellular network was available.
The second dataset was the RDD CATI survey, which took place four months after PMA2020 R5 survey. To conduct the RDD CATI survey, PMA2020 Baltimore and Institute Supérieur des Sciences de la Population (ISSP) staff trained five call center supervisors for three days. Supervisors had at least a Bachelor degree and all had previous survey research experience. Twenty-five interviewers were trained for four days and 20 interviewers were retained for data collection. All interviewers spoke French and at least one of four local languages, except for one interviewer who spoke exclusively French. Data collection was led by ISSP and took place from April 13 to May 17, 2018 in a call center located in an NGO building in Ouagadougou. Interviewers worked in two shifts, the first group from approximately 12-4 pm, the second group from 4-8 pm.
The second was refusal at consent and the third was "break-off", corresponding to a consenting respondent who completed less than 50% of questions. The final group included women who completed the interview, classified as a partial interview when 50-80% of questions were answered and a complete interview when 80% of questions or more were answered. Based on the aforementioned call disposition codes, we created four key call outcome indicators aligned with AAPOR standards-response rate, cooperation rate, refusal rate and contact rate (Table  3 ). To improve on the specificity of these outcome measures, AAPOR also recommends calculating rates that exclude an estimated number of unknown eligibility phone numbers from the denominator for response and contact rates. Based on pilot data collected in February 2018, we estimated that 20% of calls with unknown eligibility would in fact include an eligible woman.
However, the RDD survey only collected data on the five most common methods used in Burkina Faso, based on PMA2020 R5 estimates (covering 98. 8% of modern method use): implants, injectables, pills, condoms and IUDs. Thus we limited the definition of modern contraceptive use to these five methods for both the FTF and RDD surveys in this study  [18]. In addition, we constructed a five-category indicator of method mix, including the following contraceptive methods: implant, IUD, injectables, pills, and condoms. We selected independent measures related to modern contraceptive use as cited in the literature as well as factors related to phone ownership, that were collected in both surveys to conduct our analysis  [25] [26] [27]. The independent variable of interest was mode of data collection. The FTF survey was the reference group; RDD the comparison group.
Women's sociodemographic characteristics included age grouped in 5-year increments, current union status (in union-i. e. , currently married or living with a partner vs. not in union), parity (ever had a birth yes-no). residential area (urban vs. rural), educational attainment (none, primary, or secondary and higher) and language of survey (Moore, French, Dioula, Fulfulde, or Gourmantchema). Missing data. The RDD data had item non-response due to internet outages at the call center (electricity brown-outs). We used the hot deck method  [28]  to impute missing values for three variables: age (43 missing values, 1. 8%), residence (10 missing values, 0. 4%) and education (10 missing values, 0. 4%), assuming data were missing completely at random.
We examined the equivalence of modern contraceptive use prevalence estimates in the weighted RDD and FTF samples, setting an equivalence margin j À d to +/-4%. The null hypothesis assumed a difference of more than 4% between the two survey estimates. We report the 90% confidence interval for the difference in point estimates, which simulates performing two one-sided tests. We also report a p-value from an adjusted Wald test  [30]. We further compared modern contraceptive use by mode of data collection by conducting multivariable logistic regression adjusting for additional sociodemographic factors. We first assessed bi-variate relationships between each co-variate and modern contraceptive use among the pooled FTF-RDD data. We then conducted multivariable logistic regression to assess the odds of modern contraceptive use by survey mode, adjusting for covariates.
Data treatment Confirmatory factor analyses were performed with AMOS V21. The other analyses were conducted with SPSS V23. Missing data for each variable was below 2%. The Expectation-Maximization (EM) algorithm method was used to impute missing data, as this alternative to the listwise approach is considered better when missing values are less than 5%  (Allison, 2003). Results of descriptive statistics (cf. Table  1  and 3 ) indicated that the kurtosis (asymmetry) and skewness indices of each variable did not significantly deviate from the ±2 threshold of nonnormal distribution  (Gravetter & Wallnau, 2016). The subscales' Cronbach alphas were all above the recommended. 70 threshold  (Cortina, 1993).
Phase 1 -Exploratory factor analysis (EFA) A Common Factor Analysis with the principal-axis factoring (PAF) extraction method was chosen, as it is recommended to examine the quality of a scale's construct  (Beavers et al. , 2013; Costello & Osborne, 2005; Worthington & Whittaker, 2006). Oblique rotations were selected because of the high inter-correlations between the 32 variables (r >. 50, p <. 01). A Kaiser-Meyer-Olkin (KMO) coefficient above. 90 indicated a good sampling adequacy  (Worthington & Whittaker, 2006). The number of factors retained was determined with a parallel analysis procedure recommended for its effectiveness over Kaiser's criterion of eigenvalues over one  (Hayton, Allen, & Scarpello, 2004; Kahn, 2006). A parallel analysis consists in generating multiple random datasets with the same number of observations and variables as the raw data  (Watkins, 2006)  (one thousand sets here).
e. , 1. 88 cases per parameter) undermined the feasibility of a structural equation modeling (SEM) approach using observed and latent variables  (Hooper & al. , 2008; Westland, 2010; Worthington & Whittaker, 2006). Therefore, a regression-based mediation method using ordinary least squares (OLS) was implemented with the PROCESS macro 3. 2 for SPSS  (Hayes, 2018). This reliable method  (Hayes, Montoya, & Rockwood, 2017 ) uses a bootstrapping procedure to generate bias-corrected 95% confidence intervals, thus increasing the accuracy of inferences on the direct and indirect effects of each path in the models  (Hayes, 2017; Preacher & Hayes, 2008). Standard errors were based on the HC3 Heteroskedasticity Consistent Standard Error Estimator recommended by  Hayes and Cai (2007) , whether the homoskedasticity assumption is violated or not.
Acknowledgements The authors wish to thank  Sanofi France 's team of Learning & Professional Development as well as the participants for their voluntary contribution. We gratefully acknowledge the support of the training design and delivery experts in linguistics and the company's training partner Transfer, who facilitated the data collection process. We extend our thanks to  Professor Reid Bates , Director of  School of Leadership and Human Resource Development at Louisiana State University , for his authorization to use the Learning Transfer System Inventory (LTSI).
Sampling Two repeated cross-sectional surveys were conducted, one before the first distribution of cash (baseline survey, May 16 to July 4, 2014) and the other after 24 months of program operation (endline survey, May 26 to June 16, 2016) (Fig  1 ). Representative samples of mothers and their 6-to 29-month-old children in both arms of the study were surveyed in each village. This age range was the best compromise for reasonable theoretical exposure of children to the program (at least 12 months) and stage of exposure (during pregnancy or not later than 6 months of age during infancy) after 2 years of program operation (S1 Fig). In each village, households were randomly selected from the program census database. The latter was compiled prior to the beginning of the study through an exhaustive household census whose aim was to list the households eligible for CTs in each ICCM-Nut village, i.
Data collection Data were collected using the same standardized questionnaire at baseline and endline. The questionnaire was administered face-to-face to women and heads of households during home visits by experienced enumerators speaking the local languages of the study area. These enumerators were identified through a highly selective process and extensively trained over 2 weeks. Their training mainly consisted of the exhaustive review, translation, and pretest of the questionnaire; each question was standardized across the different vernacular languages spoken in the study area. Enumerators also learned how to perform anthropometric measurements and how to collect data through tablets. Built upon the program's theory of change, the questionnaire covered a wide range of intermediary outcomes meant to document the program's theoretical impact pathways, which are presented in their simplified version in Fig 2 (for a more comprehensive version, please see  [27] ).
We estimated food insecurity experienced by households over the previous 30 days using the standard Household Food Insecurity Access Scale (HFIAS)  [32]. The "health and hygiene" pathway. At the child level, we collected data on overall health since birth (as perceived by the mother), morbid episodes over the previous 15 days, and medical monitoring since birth. At the mother level, we collected information on antenatal followup, delivery, and postnatal care. In children aged less than 20 months, who had a chance to be exposed to the program in utero, we collected birth weights (BWs) from health documents when available and calculated the proportion of children with low birth weight (LBW) (BW < 2,500 g). The hygiene of individuals and their houses was assessed using spot-check observations  [33, 34].