Zapisane w:
| 1. autor: | |
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| Format: | Recurso digital |
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| Wydane: |
Zenodo
2026
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| Hasła przedmiotowe: | |
| Dostęp online: | https://doi.org/10.5281/zenodo.19449702 |
| Etykiety: |
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Spis treści:
- <p>This dissertation presents a twelve-month longitudinal case study examining whether a sole founder, operating without institutional funding, organizational staff, or legacy political infrastructure, can construct a functioning third-party civic organization in the United States through the combined use of large language model artificial intelligence, freely available government data, and open digital platforms. The subject of investigation is the American</p> <p>Humanist Party (AHP), founded March 1, 2026, by the researcher-as-founder, Marco Drummond. The study is designed as an autoethnographic, participatory action research inquiry that simultaneously constitutes and documents the organizational phenomena under examination.</p> <p>The research addresses a convergence of three contemporary democratic crises: the structural marginalization of third-party political formation through electoral law and ballot access barriers; the financialization of political participation that renders civic organization prohibitively resource-intensive; and the emergence of AI-assisted knowledge production as a potential equalizing force in democratic participation. Drawing on 133 peer-reviewed, government, and primary source citations, the dissertation synthesizes theoretical frameworks from social movement theory, deliberative democracy, behavioral economics, political philosophy, legal scholarship, environmental governance, and AI ethics to establish the evidentiary foundation for AHP's policy platform and organizational legitimacy.</p> <p>The methodology employs triangulated data collection across three streams: digital analytics measuring platform growth and civic engagement; legislative tracking quantifying policy development output; and civic engagement metrics documenting member participation and organizational capacity. Preliminary findings across the first research period suggest that AI-assisted organizational infrastructure can reduce the capital threshold for civic formation significantly, enable evidence-based policy development at scale without institutional research staff, and support multi-platform digital civic engagement strategies previously available only to well-funded political organizations.</p> <p>The dissertation contributes to literature on participatory democracy, third-party political viability, digital civic infrastructure, and the emerging role of AI in democratic participation. Implications extend to policy scholars, civic technologists, electoral reform advocates, and democratic theorists examining the conditions under which bottom-up political formation can challenge entrenched two-party electoral systems.</p>