cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15139/s3/5yqiwp
title: Replication Data for: The Policy Blame Game: How Polarization Distorts Democratic Accountability Across the Local, State, and Federal Level

description: Democratic accountability relies on voters to punish their representatives for the policies they dislike. Yet, a separation-of-powers system can make it hard to know who is to blame, and partisan biases can distort how voters assess responsibility. In the midst of the COVID-19 pandemic, precautionary measures were put into place sometimes by Governors, sometimes by Mayors, and sometimes by no one at all, allowing us to identify circumstances under which voters hold out-party vs. in-party politicians responsible for these policies. With a national survey spanning 48 states, we test our theories that attitudes toward policies and parties intersect to determine when selective attribution takes place. We find that, as individuals become increasingly opposed to a policy, they are more likely to blame whichever level of government is led by the out-party. This tendency is most pronounced among partisans with the strongest in-party biases. Our study demonstrates a troubling obstacle to democratic accountability: the intersection of a separation-of-powers system, which makes accountability cognitively difficult, and a polarized public. Overall, we provide important insight into the mechanisms that drive selective attribution and the conditions under which democratic accountability is at risk.
DOI: 10.15151/esrf-es-886870995
title: IBS BAG

description: The IBS BAG includes in this proposal IBS teams and external groups from iRTSV/CEA (Grenoble), CEA-Cadarache (St Paul lez Durance) and IRBA (Brétigny-sur-Orge). We study structure-function relationships of proteins emphasizing in human health, biotechnology and methodology. Most of the projects are a continuation of the MX-2329 proposal and can be grouped in different topics as follows: host-pathogen interaction, new drug targets, fundamental cellular mechanisms, membrane proteins, intrinsically disordered proteins, biotechnological applications and methodology. Some of these projects use integrative approaches (X-ray crystallography, SAXS, NMR (and cryo-EM), together with other biophysical studies) with the aim to fully understand the complexity of the biological macromolecular systems on study. Some teams are dedicated to serial crystallography and its developments, for which the ESRF-EBS has become the perfect tool.
DOI: 10.17909/78wg-t688
title: VV191 HST+JWST

description: VV191 data used to measure backlit dust and gravitatjonal-lens properties
DOI: 10.3886/icpsr38428.v1
title: 21st Century Policing: Cross-Site, Multi-Stakeholder Sentinel Event Review (SER) Project, United States, 2018-2021
title: Version 1

description: The 21st Century Policing: Cross-Site, Multi-Stakeholder Sentinel Event Review (SER) Project, seeks to test and learn from the application of the Sentinel Event Review methodology in police departments in a cross-site evaluation over three years. The goal is to learn how SER's can be sustained by local law enforcement organizations when working in a multi-stakeholder environment.
description: The purpose of this study is to increase knowledge and understanding of sentinel event review (SER) models, as applied to criminal justice, in order to better understand root causes that can be mitigated to reduce or eliminate critical events in complex settings with multiple stakeholders. Sentinel events can include such things as the wrongful conviction of an innocent person, premature release from prison of a dangerous offender, or even a near miss that could have led to a bad outcome if not caught.
description: The surveys were administered either in-person or via web-based surveys. For SER 1 participants, there were separate data collection periods for pre, post, and follow-up surveys. For SER 2 participants, there were separate data collection periods for pre and post/follow-up surveys. Due to time constraints, post and follow-up survey data were collected via a combined survey. For SER 2, the post/follow-up survey included a screening item that directed participants to first select which SER they participated in; they were then directed to complete the rest of the survey.
description: Not applicable
description: Response Rates: 69% response rate (9 of 13 SER team members provided data)
description: Presence of Common Scales: None
description: Datasets: DS0: Study-Level Files DS1: Sentinel Event Review 1 Outcome Data DS2: Sentinel Event Review 2 Outcome Data
description: Individuals in a police department (and other organizations) who participated in Sentinel Event Reviews. Smallest Geographic Unit: County
description: on-site questionnaire; web-based surveyAll SER 1 outcome data are included in the file named SER_1_Data.All SER 2 outcome data are included in the file named SER_2_Data.The project collected data on participant characteristics; these data are not included in the final data files.Each SPSS data file has 51 variables (unique ID, 40 outcome variables, and 10 computed outcome variables).
DOI: 10.3886/icpsr38428
title: 21st Century Policing: Cross-Site, Multi-Stakeholder Sentinel Event Review (SER) Project, United States, 2018-2021
title: Archival Version

description: The 21st Century Policing: Cross-Site, Multi-Stakeholder Sentinel Event Review (SER) Project, seeks to test and learn from the application of the Sentinel Event Review methodology in police departments in a cross-site evaluation over three years. The goal is to learn how SER's can be sustained by local law enforcement organizations when working in a multi-stakeholder environment.
description: The purpose of this study is to increase knowledge and understanding of sentinel event review (SER) models, as applied to criminal justice, in order to better understand root causes that can be mitigated to reduce or eliminate critical events in complex settings with multiple stakeholders. Sentinel events can include such things as the wrongful conviction of an innocent person, premature release from prison of a dangerous offender, or even a near miss that could have led to a bad outcome if not caught.
description: The surveys were administered either in-person or via web-based surveys. For SER 1 participants, there were separate data collection periods for pre, post, and follow-up surveys. For SER 2 participants, there were separate data collection periods for pre and post/follow-up surveys. Due to time constraints, post and follow-up survey data were collected via a combined survey. For SER 2, the post/follow-up survey included a screening item that directed participants to first select which SER they participated in; they were then directed to complete the rest of the survey.
description: Not applicable
description: Response Rates: 69% response rate (9 of 13 SER team members provided data)
description: Presence of Common Scales: None
description: Datasets: DS0: Study-Level Files DS1: Sentinel Event Review 1 Outcome Data DS2: Sentinel Event Review 2 Outcome Data
description: Individuals in a police department (and other organizations) who participated in Sentinel Event Reviews. Smallest Geographic Unit: County
description: on-site questionnaire; web-based surveyAll SER 1 outcome data are included in the file named SER_1_Data.All SER 2 outcome data are included in the file named SER_2_Data.The project collected data on participant characteristics; these data are not included in the final data files.Each SPSS data file has 51 variables (unique ID, 40 outcome variables, and 10 computed outcome variables).
DOI: 10.34740/kaggle/dsv/4139828
title: Mahanagar Yatayat Dataset
DOI: 10.5281/zenodo.6984024
title: Nutritional table to estimate the availability of nutrients in households from the Mexican National Survey of Household Income and Expenditures (ENIGH) 2008-2020

description: The database contains the amount of six nutrients (calories, proteins, vitamin A and C, iron, and zinc) per 100 grams/mililiters for each of the food categories used in the Mexican National Survey of Household Income and Expenditures 2008-2020.
description: This research was funded by the Fondo CONACYT - CONEVAL, grant number A3-S-81099. If researchers require additional information, please contact Victor Perez (victor.hernandez@ibero.mx) or Alan Hernandez (alan.hernandez@ibero.mx)
DOI: 10.5281/zenodo.6984025
title: Nutritional table to estimate the availability of nutrients in households from the Mexican National Survey of Household Income and Expenditures (ENIGH) 2008-2020

description: The database contains the amount of six nutrients (calories, proteins, vitamin A and C, iron, and zinc) per 100 grams/mililiters for each of the food categories used in the Mexican National Survey of Household Income and Expenditures 2008-2020.
description: This research was funded by the Fondo CONACYT - CONEVAL, grant number A3-S-81099. If researchers require additional information, please contact Victor Perez (victor.hernandez@ibero.mx) or Alan Hernandez (alan.hernandez@ibero.mx)
DOI: 10.5281/zenodo.7035566
title: Nutritional table to estimate the availability of nutrients in households from the Mexican National Survey of Household Income and Expenditures (ENIGH) 2008-2020

description: The database contains the amount of six nutrients (calories, proteins, vitamin A and C, iron, and zinc) per 100 grams/mililiters for each of the food categories used in the Mexican National Survey of Household Income and Expenditures 2008-2020.
description: This research was funded by the Fondo CONACYT - CONEVAL, grant number A3-S-81099. If researchers require additional information, please contact Victor Perez (victor.hernandez@ibero.mx) or Alan Hernandez (alan.hernandez@ibero.mx)
DOI: 10.5519/qd.jr1enbes
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.20732674
title: ds01_CAF_survey_performances.xlsx

description: The excel file contains the results from the Capitals Approach Framework (CAF) survey, which were further used for the FCM attributes (see ds03_FCM_attributes) for a leverage points analysis.
DOI: 10.6084/m9.figshare.20732674.v1
title: ds01_CAF_survey_performances.xlsx

description: The excel file contains the results from the Capitals Approach Framework (CAF) survey, which were further used for the FCM attributes (see ds03_FCM_attributes) for a leverage points analysis.
DOI: 10.6084/m9.figshare.20732677
title: ds02_FCM_adjacency_matrix.csv

description: The excel sheet contains the adjacency matrix showing the relationships between governance processes used for further leverage points analysis.
DOI: 10.6084/m9.figshare.20732677.v1
title: ds02_FCM_adjacency_matrix.csv

description: The excel sheet contains the adjacency matrix showing the relationships between governance processes used for further leverage points analysis.
DOI: 10.6084/m9.figshare.20732680
title: ds03_FCM_attributes.csv

description: The file displays the results from the Capitals Approach Framework (CAF) survey, indicating the performance of different governance processes, used in the leverage points analysis.
DOI: 10.6084/m9.figshare.20732680.v1
title: ds03_FCM_attributes.csv

description: The file displays the results from the Capitals Approach Framework (CAF) survey, indicating the performance of different governance processes, used in the leverage points analysis.
DOI: 10.5519/qd.spz2e6p7
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (130 records)
DOI: 10.5517/ccdc.csd.cc2b9dz1
title: CCDC 2154003: Experimental Crystal Structure Determination

description: Related Article: Ivan A. Buldashov, Alexander G. Medvedev, Alexey A. Mikhaylov, Andrei V. Churakov, Ovadia Lev, Petr V. Prikhodchenko|2022|CrystEngComm|24|6101|doi:10.1039/D2CE01017H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b9f14
title: CCDC 2154005: Experimental Crystal Structure Determination

description: Related Article: Ivan A. Buldashov, Alexander G. Medvedev, Alexey A. Mikhaylov, Andrei V. Churakov, Ovadia Lev, Petr V. Prikhodchenko|2022|CrystEngComm|24|6101|doi:10.1039/D2CE01017H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.20468667
title: Table_S1_EpigenMast_cow_sampling.xlsx

description: the besic backgroup information of selected cows
DOI: 10.6084/m9.figshare.20468667.v1
title: Table_S1_EpigenMast_cow_sampling.xlsx

description: the besic backgroup information of selected cows
DOI: 10.6084/m9.figshare.20562633
title: Assisted voting data from Chilean Presidential and Constitutional Convention election in 2021

description: The raw data can be imported in an R environment by sourcing the data.R file. This handles reading the raw CSV file coming from REDCap along with the original labeling and formatting information; there is a final cleanup before the dataset is ready for processing. <br> --- <br> The present study aims to describe and discuss the voting experiences of people with disabilities in Chile during two of the national elections which took place in 2021. This study explores whether people with disabilities in Chile know and use assisted voting, the main legal tool at their disposal to facilitate their right to vote. The results suggest that despite the existence of legal provisions and special protocols created to facilitate voting for people with disabilities, there are still multiple barriers that hinder their interaction with the Chilean electoral system. While some barriers are related to non-compliance of provisions and protocols, pointing to implementation gaps, other barriers are related to the design of the electoral system, suggesting the need to push for its reform to create a more inclusive electoral system.
DOI: 10.6084/m9.figshare.20562633.v1
title: Data [raw responses from REDCap]

description: The raw data can be imported in an R environment by sourcing the data.R file. This handles reading the raw CSV file coming from REDCap along with the original labeling and formatting information; there is a final cleanup before the dataset is ready for processing. <br> --- <br> The present study aims to describe and discuss the voting experiences of people with disabilities in Chile during two of the national elections which took place in 2021. This study explores whether people with disabilities in Chile know and use assisted voting, the main legal tool at their disposal to facilitate their right to vote. The results suggest that despite the existence of legal provisions and special protocols created to facilitate voting for people with disabilities, there are still multiple barriers that hinder their interaction with the Chilean electoral system. While some barriers are related to non-compliance of provisions and protocols, pointing to implementation gaps, other barriers are related to the design of the electoral system, suggesting the need to push for its reform to create a more inclusive electoral system.
DOI: 10.34740/kaggle/ds/2443664
title: Biome Cerrado Dataset - CerraData
DOI: 10.17632/ngw73ny3yd.1
title: ICCM DIB

description: A dataset describing the use of Indigenous Crime Control Mechanisms in crime prevention in Selected Communities in North Central Nigeria. The data shows response rates from the selected communities, the preference for indigenous  crime control mechanisms for crime prevention.
DOI: 10.17632/mhrzbc58p7.1
title: Characterization of psoriasis phenotypes in patients requiring systemic treatment

description: This data set was used to identify, by using latent class analysis, the underlying phenotypes that best explain the observed heterogeneity within the national Italian Registry of psoriasis (PsoReal).
DOI: 10.5281/zenodo.8093745
title: MNIST-Federated-Learning

description: Please find below the descriptions of the three configurations for partitioning <strong>the MNIST Train dataset into 10 clients and the MNIST Train data: </strong><br> <strong>Balanced Distribution:</strong> In the first configuration, the MNIST dataset is partitioned among 10 clients in a balanced manner. This means that the data samples from each class are evenly distributed among the clients. Each client receives a roughly equal number of images from each digit class, ensuring that the distribution of samples across clients is proportional and representative of the overall dataset. <strong> [ Config 1]</strong> <strong>Heterogeneous Distribution (One Class per Client)</strong>: In the second configuration, the MNIST dataset is partitioned in a heterogeneous manner, where each client is assigned a single digit class exclusively. This means that one client will only receive images of the digit '0', another client will receive images of the digit '1', and so on. In this setup, each client becomes an expert in classifying a specific digit, allowing for specialized training and evaluation. <strong>[ Config 2]</strong> <strong>Mixed Distribution:</strong> In the third configuration, the MNIST dataset is partitioned using a mixed distribution approach. This means that the data samples from all digit classes are distributed among the 10 clients, but the distribution is not necessarily balanced. The number of samples assigned to each client may vary for different digit classes, resulting in an uneven distribution across the clients. This configuration aims to capture both the overall diversity of the dataset and the varying difficulty levels of classifying different digits. <strong>[ Config 3 ]</strong> <strong>The structure of "Mnist-dataset" folder is </strong><em><strong>:</strong></em><br> Mnist-dataset/<br> ├── config1/<br> │ ├── client-1/<br> │ │ └── client_1_config1.csv<br> │ ├── client-2/<br> │ │ └── client_2_config1.csv<br> │ ├── client-3/<br> │ │ └── client_3_config1.csv<br> │ └── ...<br> ├── config2/<br> │ ├── client-1/<br> │ │ └── client_1_config2.csv<br> │ ├── client-2/<br> │ │ └── client_2_config2.csv<br> │ ├── client-3/<br> │ │ └── client_3_config2.csv<br> │ └── ...<br> ├── config3/<br> │ ├── client-1/<br> │ │ └── client_1_config3.csv<br> │ ├── client-2/<br> │ │ └── client_2_config3.csv<br> │ ├── client-3/<br> │ │ └── client_3_config3.csv<br> │ └── ...<br> └── mnist_test.csv<br>
description: {"references": ["DENG, Li. The mnist database of handwritten digit images for machine learning research [best of the web]. IEEE signal processing magazine, 2012, vol. 29, no 6, p. 141-142."]}
DOI: 10.5281/zenodo.8094174
title: MNIST-Federated-Learning

description: Please find below the descriptions of the three configurations for partitioning <strong>the MNIST Train dataset into 10 clients and the MNIST Train data: </strong><br> <strong>Balanced Distribution:</strong> In the first configuration, the MNIST dataset is partitioned among 10 clients in a balanced manner. This means that the data samples from each class are evenly distributed among the clients. Each client receives a roughly equal number of images from each digit class, ensuring that the distribution of samples across clients is proportional and representative of the overall dataset. <strong> [ Config 1]</strong> <strong>Heterogeneous Distribution (One Class per Client)</strong>: In the second configuration, the MNIST dataset is partitioned in a heterogeneous manner, where each client is assigned a single digit class exclusively. This means that one client will only receive images of the digit '0', another client will receive images of the digit '1', and so on. In this setup, each client becomes an expert in classifying a specific digit, allowing for specialized training and evaluation. <strong>[ Config 2]</strong> <strong>Mixed Distribution:</strong> In the third configuration, the MNIST dataset is partitioned using a mixed distribution approach. This means that the data samples from all digit classes are distributed among the 10 clients, but the distribution is not necessarily balanced. The number of samples assigned to each client may vary for different digit classes, resulting in an uneven distribution across the clients. This configuration aims to capture both the overall diversity of the dataset and the varying difficulty levels of classifying different digits. <strong>[ Config 3 ]</strong> <strong>The structure of "Mnist-dataset" folder is </strong><em><strong>:</strong></em><br> Mnist-dataset/<br> ├── config1/<br> │ ├── client-1/<br> │ │ └── client_1_config1.csv<br> │ ├── client-2/<br> │ │ └── client_2_config1.csv<br> │ ├── client-3/<br> │ │ └── client_3_config1.csv<br> │ └── ...<br> ├── config2/<br> │ ├── client-1/<br> │ │ └── client_1_config2.csv<br> │ ├── client-2/<br> │ │ └── client_2_config2.csv<br> │ ├── client-3/<br> │ │ └── client_3_config2.csv<br> │ └── ...<br> ├── config3/<br> │ ├── client-1/<br> │ │ └── client_1_config3.csv<br> │ ├── client-2/<br> │ │ └── client_2_config3.csv<br> │ ├── client-3/<br> │ │ └── client_3_config3.csv<br> │ └── ...<br> └── mnist_test.csv<br>
description: {"references": ["DENG, Li. The mnist database of handwritten digit images for machine learning research [best of the web]. IEEE signal processing magazine, 2012, vol. 29, no 6, p. 141-142."]}