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Record W4389206380 · doi:10.22215/etd/2023-15852

Forgery for Freedom: Enslaved Literacy and Resistance in the British Caribbean

2023· dissertation· en· W4389206380 on OpenAlexaff
Haley Dawn North

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicCaribbean history, culture, and politics
Canadian institutionsCarleton University
Fundersnot available
KeywordsColonialismLiteracyConversationFunctional illiteracyResistance (ecology)HistoriographyCognitive reframingObedienceHistorySociologyGender studiesPolitical scienceLawPedagogyPsychologyEcology

Abstract

fetched live from OpenAlex

This project explores enslaved avenues towards literacy and their utilization of literacy skills in resistance efforts through the Eurocentric structures within the plantation societies of Barbados and Jamaica during the late eighteenth and into the early nineteenth century. This work offers a greater understanding of enslaved literacy and illiteracy, literate enslaved navigation of their enslavement and resistance, and British colonial laws’ complicated relationship with enslaved education. Furthermore, it adds a new perspective on the enslaveds’ relationship with literacy to existing historiography on Black literacy education in the British Caribbean by reframing the existing conversation on enslaved education and obedience through the white colonial lens. Instead, it puts forward the connections between enslaved literacy education, anti-colonial knowledge, enslaved resistance, and large-scale revolt at the forefront of the historical conversation on enslaved resistance.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.636
Threshold uncertainty score0.732

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0140.013
Scholarly communication0.0080.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.022
GPT teacher head0.315
Teacher spread0.293 · 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
Published2023
Admission routes1
Has abstractyes

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