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  • Immersive Inclusion: Diversity and Inclusion Training Using Virtual Reality

    Document thumbnail: Immersive Inclusion: Diversity and Inclusion Training Using Virtual Reality
    Type:
    Document
    Descripción/Resumen:
    An exploration of the use of virtual reality technology in the context of diversity and inclusion training. This manuscript describes two studies: Study 1 was longitudinal and investigated the impacts of a VR-based bias training. Cognitive and affective empathy levels and impact on behavior, attitude, and knowledge before and after the training were measured to test the hypotheses that (H1) cognitive empathy levels would increase and (H2) individuals with higher initial levels of empathy would demonstrate more pronounced changes in cognitive empathy following the training. H1 was supported but larger changes were found in affective empathy levels. H2 was also supported as individuals with higher initial empathy levels showed higher levels of cognitive empathy after the training compared to individuals with lower initial empathy levels. However, again, larger differences were found in affective empathy levels. Qualitative data revealed a lasting impact nine weeks after the training that was not present in the quantitative data. Study 2 surveyed healthcare professionals who previously participated in a VR-based DEI training that focused on social determinants of health and empathy in healthcare professionals. The purpose of this study was to gain insight into the longitudinal impacts of a VR-based DEI training by gathering qualitative data from the participants at least a year after they went through the training. The respondents reported a lasting influence from the training. Reasons for the discrepancy between the qualitative and quantitative results are discussed as are implications for organizations and future DEI training development and research.
    Creador/Autor:
    Mason, Lauren
    Peticionario:
    Lauren Mason
    Fecha modificada:
    02/08/2023
    Fecha modificada:
    02/08/2023
    Fecha de creacion:
    2022
    Licencia:
    Attribution 4.0 International

  • Coherence_Evaluations - nvl_pollution.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_pollution.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    11/12/2022
    Fecha modificada:
    11/12/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_earth.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_earth.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    11/12/2022
    Fecha modificada:
    11/12/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_climate.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_climate.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    11/12/2022
    Fecha modificada:
    11/12/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_environmental.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_environmental.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    11/12/2022
    Fecha modificada:
    11/12/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • TV News Transcripts of Outer Space Coverage

    Dataset thumbnail: TV News Transcripts of Outer Space Coverage
    Type:
    Dataset
    Descripción/Resumen:
    Text and Metadata for 14,399 newspaper articles. Transcripts collected from Internet Archive Date Range: 2010-2022 File includes meta/data: - Unique-id (uid) - Title (incl. search term) - Date - Link (url) - Abstract - Text Text matching the following terms: - space explor* - space mission - space science - spaceship - space tour* - space transport* - spacecraft - space shuttle - outer space - astronom* - astrop* - astrona* - planet - NASA - star trek - star wars - lunar - space flight
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    11/12/2022
    Fecha modificada:
    11/12/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Newspaper coverage of Outer Space Theme

    Dataset thumbnail: Newspaper coverage of Outer Space Theme
    Type:
    Dataset
    Descripción/Resumen:
    Text and Metadata for 9,061 newspaper articles. Newspapers included: New York Times, Wall Street Journal, & Washington Post Date Range: 2017-2022 File includes meta/data: - Unique-id (uid) - Title (incl. source paper & section name) - Date - Link (url) - Author - Text Text matching the following terms: - space explor* - space mission - space science - spaceship - space tour* - space transport* - spacecraft - space shuttle - outer space - astronom* - astrop* - astrona* - planet - NASA - star trek - star wars - lunar - space flight
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    11/12/2022
    Fecha modificada:
    11/12/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_random5k.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_random5k.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    11/05/2022
    Fecha modificada:
    11/11/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - pmc_environmental.csv

    Dataset thumbnail: Coherence_Evaluations - pmc_environmental.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    11/04/2022
    Fecha modificada:
    11/04/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - pmc_earth.csv

    Dataset thumbnail: Coherence_Evaluations - pmc_earth.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    11/04/2022
    Fecha modificada:
    11/04/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)