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Record W4396569856 · doi:10.22215/etd/2024-15944

“As if They Were from Over There”: The Insufficiency of Documentation as a Means of Securing Citizenship Rights for Dominicans of Haitian Descent

2024· dissertation· en· W4396569856 on OpenAlexaff
Allison Marie Kingston

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicCaribbean and African Literature and Culture
Canadian institutionsCarleton University
Fundersnot available
KeywordsCitizenshipDocumentationDescent (aeronautics)Political scienceGenealogyLawHistoryGeographyComputer sciencePoliticsProgramming language

Abstract

fetched live from OpenAlex

As decades of political change by various governments of the Dominican Republic have created a situation of denationalization for thousands of Dominicans of Haitian descent, documentation is often sought as a solution for this statelessness. However, considering historical context and systemic barriers, this thesis exposes the stark reality that documentation alone fails to protect the citizenship rights of Dominicans of Haitian descent. Through semi-structured interviews and ethnographic observations, this research delves into the impact of anti-Blackness on the citizenship rights of individuals of Haitian descent in the Dominican Republic, irrespective of their documentation status. The thesis argues that possession of legal documentation does not fully protect individuals from state violence. Rather, it explores the gendered patterns of physical and administrative violence against people of Haitian descent. Additionally, it investigates obstacles to accessing livelihoods and underscores the inadequacy of documentation in preventing labour abuse.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.012
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.256
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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