cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/ib504i
title: Replication Data for: Reconceptualizing Political Knowledge: Race, Ethnicity, and Carceral Violence

description: What is political knowledge? This paper argues that the traditional measure of political knowledge is limited, as it represents one domain of facts that people should know about American politics. This domain of knowledge is rooted in the liberal-democratic face of the state and neglects other political knowledge generated from the carceral face of the state. We argue that knowledge of carceral violence, especially against African Americans, represents a separate domain of knowledge that is particularly relevant to marginalized communities, especially Black youth. Once we include carceral violence in our measures of political knowledge, established patterns of whites having more political knowledge than Blacks are reversed. Using a novel measurement strategy and based on a nationally representative survey of over 2,000 young people, we find that knowledge of carceral violence is distinct from measures of what has been called general political knowledge. Finally, we find, knowledge of carceral violence has distinct correlates from the standard knowledge battery and its relationship to political participation varies by racial group but tends to depress the political participation of African Americans. Our findings raise the question of what comprises relevant and important political knowledge today and for which communities.
DOI: 10.7910/dvn/mh9mpj
title: Social Conflict Analysis Dataset - Organizational Properties

description: This is an extension of the Social Conflict Analysis Database, providing identifying information for organizations and identity groups contained in the original SCAD. Countries covered include Egypt, Nigeria, Kenya, South Africa, Mexico, Haiti, and the Dominican Republic.
DOI: 10.7910/dvn/nvyczr
title: WSUParkingDemandData

description: Hourly lot-level parking data from WSU Transportation Services (Pullman, WA) from 2019-2021.
description: http://hdl.handle.net/1773/49978
DOI: 10.7910/dvn/rqzq1q
title: Cannabis Tolerance Break: T-Break Guide Study

description: Dataset of the Cannabis Tolerance Break, T-Break Guide Study. 143 current cannabis user were recruited to take a 21 day break from cannabis. They were offered the T-Break Guide (go.uvm.edu/tbreak) as a resource but were not required to use it. Participants completed a baseline survey prior to their break, and a follow-up survey 30 days later. This study was IRB approved at the University of Vermont; participant informed consent included that non-identifiable data could be stored and used for other research. Research manuscript titled “Feasibility and Utility of a Structured Guide for Cannabis Tolerance Breaks in Young Adults “ available opensource at http://dx.doi.org/10.1080/07448481.2022.2155061. 

Please contact Tom Fontana (tom.fontana@uvm.edu) with questions.
DOI: 10.7910/dvn/xpeslb
title: Replication Data for: Public health impacts of an imminent Red Sea oil spill

description: Replication Data for: Public health impacts of an imminent Red Sea oil spill
DOI: 10.7910/dvn/yp1d9d
title: Replication Data for: "Long-term Investors, Demand Shifts, and Yields", Jansen (2024)

description: This package provides STATA (version 18.0 STATAMP) codes, MATLAB (version R2023A) codes, and pseudo data to reproduce tables in Jansen (2024): “Long-term Investors, Demand Shifts, and Yields”. Notice that all the data is pseudo data as the original data is strictly proprietary.
DOI: 10.7910/dvn/dmvzaw
title: Executive Agreements Database, Background Statement Concerning the Agreement Between The United States and The Russian Federation Amending and Extending The Agreement Of May 31, 1988, On Mutual Fisheries Relations, with Annex Effected By Exchange Of Notes Act Washington March 11 & September 15, 1993 Entered Into Force April 4, 1994

description: TIAS 12172 cover memo
DOI: 10.7910/dvn/j0xmmr
title: Randomized Control Trial Endline Data on Use of Improved Efficient Cookstoves in Mozambique

description: This survey was conducted to collect endline data for a randomized control trial, two years after the introduction of the improved cookstoves in the Angonia District of Mozambique. A similar endline study was also conducted in Malawi in the district of Dedza. Angonia district in Mozambique was selected because it shares a transboundary with the Dedza district in Malawi and has similar biophysical and socioeconomic conditions. This selection was intended because the project was set out to examine how differences in policies in these two countries contributed to the adoption and use of improved cookstoves under a randomized control trial experiment.
description: Household- and Community-level Surveys
description: This dataset was prepared for public distribution with support from the CGIAR Research Program on Water, Land and Ecosystems.
DOI: 10.7910/dvn/lfwgkz
title: Replication Data for: Populist Radical Parties, Pariahs, and Coalition Bargaining Delays

description: Replication files for the article ‘Populist Radical Parties, Pariahs, and Coalition Bargaining Delays’, forthcoming in Party Politics.
DOI: 10.7910/dvn/mh6fcc
title: (30) Descriptions of People (DOP)

description: Descriptions of People (DOP)
DOI: 10.7910/dvn/nx5mxq
title: Burundi (2007): Etude sur les determinants de l'utilisation consistante du condom chez les femmes professionnelles du sexe avec leurs clients. Premier Passage.

description: Cette etude avait pour objectif de collecter les informations sur les determinants d'opportunite, de capacite, et de motivation qui influencent l'utilisation consistante du condom chez la cible des professionelles du sexe. Au total 1187 PS ont ete enquetees utilisant un questionnaire qui a couvert les aspects tels que les caracteristiques sociodemographiques, les activites sexuelles selon les types de partenaires, les determinants de l'utilisation du condom et les indicateurs du cadre logique. Les analyses ont suivi les etapes des toolkits pour le tableau de suivi et de segmentation.
DOI: 10.7910/dvn/ahysl2
title: Thailand (2006): HIV/AIDS TRaC Study among Injecting Drug Users in Bangkok, Chiang Mai, and Chiang Rai Second Round

description: 1) To examine trends in needle sharing, equipment injection sharing at last injection, and consistent condom use with each partner type; 2) To track changes in behavioral determinants (OAM- Opportunity, Ability and Motivation) from the baseline segmentation table as well as logical framework indicators; and 3) To determine whether an association exists between exposure to PSI's interventions and significant changes in behavior and OAM factors found in the monitoring dashboard. Respondent-Driven Sampling (RDS) was used to collect data among 400 IDUs aged 15 to 45 who live or work in urban areas in Bangkok, Muang Chiang Mai District, and Muang Chiang Rai District. A screening questionnaire and self-administered questionnaire served as survey tools. The questionnaire collected information on demographic characteristics, needle-sharing practices, personal drug use, beliefs and knowledge about HIV infection, sexual practices and condom use, and exposure to PSI products and interventions. UNIANOVA analyses were performed to identify significant trends in behavior, determinants, and the impact of PSI's interventions on behavior and determinants.
DOI: 10.7910/dvn/fbvlim
title: Executive Agreements Database, Statement Regarding the Protocol Extending The Agreement Between The United States and Japan On Cooperation In Research and Development In Science and Technology Signed At Washington July 19, 2004

description: KAV 7294

First signed 07/14/2004
Last signed 07/14/2004
Entry into force (supplemented by last signed) 07/20/2004

stamped

cover memo
DOI: 10.7910/dvn/gqrsul
title: Party system volatility in post-Communist Europe

description: In their 2014 article in the British Journal of Political Science, Eleanor Neff Powell and Joshua A. Tucker examine the determinants of party system volatility in post-communist Europe. Their central conclusion is that replacement volatility – volatility caused by new party entry and old party exit – is driven by longterm economic performance. We show that this conclusion is based entirely on a miscalculation of the long-term economic performance of a single country, Bosnia-Herzegovina. Our reanalysis suggests that we know little about what causes party system volatility in post-communist Europe. Given the negative consequences traditionally associated with party system volatility, this area of research cries out for new theoretical development.
DOI: 10.7910/dvn/gveu25
title: Replication Data for: Intrinsic Motivation in Public Service: Theory and Evidence from State Supreme Courts

description: This paper provides a theoretical and empirical analysis of the intrinsic preferences of state appellate court judges. We construct a panel data set using published decisions from all state supreme courts from 1947 to 1994. We estimate the effects of changes in judge employment conditions on a number of measures of judicial performance. The results are consistent with the hypothesis that judges are intrinsically motivated to provide high-quality decisions, and that at the margin they prefer quality over quantity. When judges face less time pressure -- whether from the introduction of an intermediate appellate court, the weakening of electoral demands, or an increased judge salary -- they write more well-researched opinions that are cited more often by later judges. These effects are strongest when judges have more discretion to select their case portfolio.
DOI: 10.15468/dl.954euu
title: Occurrence Download

description: A dataset containing 127838 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Elymus caninus"
 ]
}

 The dataset includes 127838 records from 1007 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049745-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wv7e5n
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is ",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025007-250811113504898/datasets/export for details.
DOI: 10.5281/zenodo.16903370
title: Data Responden Kelompok 4

description: 505 responden dari kuesioner kelompok 4, periode pengambilan data dari 31 Juli 2025 sampai 15 Agustus 2025
DOI: 10.5281/zenodo.16912188
title: Data Responden Kelompok 4

description: 505 responden dari kuesioner kelompok 4, periode pengambilan data dari 31 Juli 2025 sampai 15 Agustus 2025
DOI: 10.15468/dl.9v4a8r
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Winteria telescopa Brauer, 1901",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((-0.0352 28.8496,-9.0352 28.8496,-9.0352 19.8496,-0.0352 19.8496,-0.0352 28.8496))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010078-250525065834625/datasets/export for details.
DOI: 10.15468/dl.6zy6hx
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rumex acetosella L.",
 "Country is Albania"
 ]
}

 The dataset includes 14 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010290-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25625/kqsiv7/zcpnbl
title: XPS_BiVO4_195_after_pec_quant.vms

description: :unav
DOI: 10.25625/kqsiv7/zibzqj
title: BiVO4-191 - CV Data and Polynom Fits.opju

description: :unav
DOI: 10.25625/kqsiv7/flaeuw
title: BiVO4-191 Bi-CV - Ring-Disk.opju

description: :unav
DOI: 10.25625/kqsiv7/hvtsyc
title: XPS_BiVO4-195_pristine_quant.vms

description: :unav
DOI: 10.25625/kqsiv7/u1k6zo
title: XRD_PS063-STONb-BiOV4.xy

description: :unav
DOI: 10.25625/kqsiv7/8aedfd
title: BiVO4 CV ring switch on analysis.opju

description: :unav
DOI: 10.25625/kqsiv7/uwlxiy
title: BiVO4 CV ring switch off analysis.opju

description: :unav
DOI: 10.25625/kqsiv7/4azmai
title: Timeconstant analysis disk anodic 3 exp fit V2.0.opju

description: :unav
DOI: 10.25625/kqsiv7/ovdhml
title: Timeconstant analysis disk anodic 3 exp fit.opju

description: :unav
DOI: 10.25625/kqsiv7
title: Replication Data for: Time-resolved photo-electrochemical measurements to study band bending of BiVO4 photoanodes

description: Replication raw data for "Time-resolved photo-electrochemical measurements to study band bending of BiVO4 photoanodes" (2025). The files include the Origin Pro timeconstant fit data for chopped illumination CV measurements and all the figures for the dark, light and chopped illumination ring-disk CV measurements. The raw XRD 2theta Scan and the XPS quantification vms file for CasaXPS.
DOI: 10.6084/m9.figshare.30962309.v1
title: <b>PGFID: A Labeled Image Dataset of Native Persian Gulf Fish Families for Machine Learning and Ecological Research</b>

description: <b>Accurate identification of fish families is fundamental to biodiversity assessment, sustainable fisheries management, and ecological monitoring; however, conventional taxonomic workflows remain time-consuming, expert-dependent, and difficult to scale. We present the Persian Gulf Fish Image Dataset (PGFID), a curated collection of 1,350 labeled images spanning 35 distinct fish families native to the Persian Gulf. The dataset includes 942 training images and 408 validation images, all captured in Bushehr (Iran) fish markets between December 2024 and June 2025 using two smartphones (iPhone 13 Pro Max and Samsung Galaxy A05s) under varying backgrounds, lighting conditions, and poses to reflect realistic field environments. Local market names provided by experienced vendors were mapped to scientific family-level labels through cross-referencing taxonomic resources such as FishBase. PGFID serves as a valuable resource for advancing image-based classification, ecological monitoring, and intelligent fisheries systems, supporting research communities working at the intersection of artificial intelligence, marine biology, and biodiversity conservation.</b>
DOI: 10.6084/m9.figshare.30962309
title: <b>PGFID: A Labeled Image Dataset of Native Persian Gulf Fish Families for Machine Learning and Ecological Research</b>

description: <b>Accurate identification of fish families is fundamental to biodiversity assessment, sustainable fisheries management, and ecological monitoring; however, conventional taxonomic workflows remain time-consuming, expert-dependent, and difficult to scale. We present the Persian Gulf Fish Image Dataset (PGFID), a curated collection of 1,350 labeled images spanning 35 distinct fish families native to the Persian Gulf. The dataset includes 942 training images and 408 validation images, all captured in Bushehr (Iran) fish markets between December 2024 and June 2025 using two smartphones (iPhone 13 Pro Max and Samsung Galaxy A05s) under varying backgrounds, lighting conditions, and poses to reflect realistic field environments. Local market names provided by experienced vendors were mapped to scientific family-level labels through cross-referencing taxonomic resources such as FishBase. PGFID serves as a valuable resource for advancing image-based classification, ecological monitoring, and intelligent fisheries systems, supporting research communities working at the intersection of artificial intelligence, marine biology, and biodiversity conservation.</b>
DOI: 10.15468/y3u9g5
title: First record of subgenus Corynopus Lepeletier and Brullé, 1835 (Genus Rhopalum Stephens, Hymenoptera: Crabronidae: Crabronini) from India: a new species and a key to Asian species of the subgenus

description: This dataset contains the digitized treatments in Plazi based on the original journal article Saini, Varun, Dey, Debjani (2024): First record of subgenus Corynopus Lepeletier and Brullé, 1835 (Genus Rhopalum Stephens, Hymenoptera: Crabronidae: Crabronini) from India: a new species and a key to Asian species of the subgenus. Zootaxa 5507 (3): 467-477, DOI: 10.11646/zootaxa.5507.3.5, URL: http://dx.doi.org/10.11646/zootaxa.5507.3.5AbstractThe subgenus Corynopus Lepeletier de Saint Fargeau and Brullé, 1835 of the genus Rhopalum Stephens, 1829 is recorded for the first time from India. A new species, viz., Rhopalum (Corynopus) chettalicum, (India: Karnataka) is described. A key and the checklist of all Asian species of the subgenus Corynopus are provided.
DOI: 10.34740/kaggle/dsv/14622983
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.21979/n9/h2xajv
title: Data of paper: Multicolor X-rays from free electron-driven van der Waals heterostructures

description: Data of paper: Multicolor X-rays from free electron-driven van der Waals heterostructures
DOI: 10.6084/m9.figshare.28473768.v2
title: Statistical Inference for High-Dimensional Convoluted Rank Regression

description: High-dimensional penalized rank regression is a powerful tool for modeling high-dimensional data due to its robustness and estimation efficiency. However, the non-smoothness of the rank loss brings great challenges to the computation. To solve this critical issue, high-dimensional convoluted rank regression has been recently proposed, introducing penalized convoluted rank regression estimators. However, these developed estimators cannot be directly used to make inference. In this article, we investigate the statistical inference problem of high-dimensional convoluted rank regression. The use of U-statistic in convoluted rank loss function presents challenges for the analysis. We begin by establishing estimation error bounds of the penalized convoluted rank regression estimators under weaker conditions on the predictors. Building on this, we further introduce a debiased estimator and provide its Bahadur representation. Subsequently, a high-dimensional Gaussian approximation for the maximum deviation of the debiased estimator is derived, which allows us to construct simultaneous confidence intervals. For implementation, a novel bootstrap procedure is proposed and its theoretical validity is also established. Finally, simulation and real data analysis are conducted to illustrate the merits of our proposed methods. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.28590277
title: Positive and Unlabeled Data: Model, Estimation, Inference, and Classification

description: This study introduces a new approach to addressing the positive and unlabeled (PU) data through the double exponential tilting model (DETM) under a transfer learning framework. Traditional methods often fall short because they only apply to the common distributions (CD) PU data (also known as the selected completely at random PU data), where the labeled positive and unlabeled positive data are assumed to be from the same distribution. In contrast, our DETM’s dual structure effectively accommodates the more complex and underexplored different distribution (DD) PU data (also known as the selected at random PU data), where the labeled and unlabeled positive data can be from different distributions. We rigorously establish the theoretical foundations of DETM, including identifiability, parameter estimation, and asymptotic properties. Additionally, we move forward to statistical inference by developing a goodness-of-fit test for the CD assumption and constructing confidence intervals for the proportion of positive instances in the target domain. We leverage an approximated Bayes classifier for classification tasks, demonstrating DETM’s robust performance in prediction. Through theoretical insights and practical applications, this study highlights DETM as a comprehensive framework for addressing the challenges of PU data.Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.28590277.v1
title: Positive and Unlabeled Data: Model, Estimation, Inference, and Classification

description: This study introduces a new approach to addressing the positive and unlabeled (PU) data through the double exponential tilting model (DETM) under a transfer learning framework. Traditional methods often fall short because they only apply to the common distributions (CD) PU data (also known as the selected completely at random PU data), where the labeled positive and unlabeled positive data are assumed to be from the same distribution. In contrast, our DETM’s dual structure effectively accommodates the more complex and underexplored different distribution (DD) PU data (also known as the selected at random PU data), where the labeled and unlabeled positive data can be from different distributions. We rigorously establish the theoretical foundations of DETM, including identifiability, parameter estimation, and asymptotic properties. Additionally, we move forward to statistical inference by developing a goodness-of-fit test for the CD assumption and constructing confidence intervals for the proportion of positive instances in the target domain. We leverage an approximated Bayes classifier for classification tasks, demonstrating DETM’s robust performance in prediction. Through theoretical insights and practical applications, this study highlights DETM as a comprehensive framework for addressing the challenges of PU data.Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.28473768
title: Statistical Inference for High-Dimensional Convoluted Rank Regression

description: High-dimensional penalized rank regression is a powerful tool for modeling high-dimensional data due to its robustness and estimation efficiency. However, the non-smoothness of the rank loss brings great challenges to the computation. To solve this critical issue, high-dimensional convoluted rank regression has been recently proposed, introducing penalized convoluted rank regression estimators. However, these developed estimators cannot be directly used to make inference. In this article, we investigate the statistical inference problem of high-dimensional convoluted rank regression. The use of U-statistic in convoluted rank loss function presents challenges for the analysis. We begin by establishing estimation error bounds of the penalized convoluted rank regression estimators under weaker conditions on the predictors. Building on this, we further introduce a debiased estimator and provide its Bahadur representation. Subsequently, a high-dimensional Gaussian approximation for the maximum deviation of the debiased estimator is derived, which allows us to construct simultaneous confidence intervals. For implementation, a novel bootstrap procedure is proposed and its theoretical validity is also established. Finally, simulation and real data analysis are conducted to illustrate the merits of our proposed methods. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.