Leveraging Data Analytics to Assess and Promote Diversity in Cultural Institutions

  1. Evi Togia

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Abstract

This research sets out to explore how data analytics can be harnessed to assess and promote diversity within cultural institutions. By examining patterns of engagement and representation across demographic groups, the study aims to provide a comprehensive understanding of inclusivity in cultural participation. The approach combines quantitative and qualitative methodologies, leveraging statistical analysis, machine learning, and thematic coding to extract insights from diverse data sources. Collaboration with cultural institutions will ensure the relevance and applicability of the findings. The anticipated outcomes include actionable recommendations for enhancing diversity and inclusion, as well as broader contributions to cultural informatics and policy development. Ultimately, the research aspires to foster more equitable and representative cultural ecosystems that reflect the richness of contemporary society.

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  1. PREreview

    This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/17254357.

    Does the introduction explain the objective of the research presented in the preprint? Yes
    Are the methods well-suited for this research? Neither appropriate nor inappropriate I see only the model names and not their implementation and quantitative results.
    Are the conclusions supported by the data? Neither supported nor unsupported No conclusions aren't supported by data
    Are the data presentations, including visualizations, well-suited to represent the data? Neither appropriate and clear nor inappropriate and unclear I dont see any visualizations in this paper
    How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Neither clearly nor unclearly I don't see a clear way that was explained in this paper
    Is the preprint likely to advance academic knowledge? Not likely
    Would it benefit from language editing? No
    Would you recommend this preprint to others? No, it's of low quality or is majorly flawed
    Is it ready for attention from an editor, publisher or broader audience? No, it needs a major revision Need quantitative impact and strong evidence

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they did not use generative AI to come up with new ideas for their review.

  2. Version published to 10.20944/preprints202509.2250.v1