FROM MORAL CONDEMNATION TO ECONOMIC STRATEGIES: REFRAMING THE END OF THE BRITISH TRANSATLANTIC SLAVE TRADE
Bibliographic record
Abstract
Why did Great Britain abolish the transatlantic slave trade in 1807, after a nearly twenty-year social movement campaign to end it? This question still continues to puzzle scholars despite the vast amount of historical research conducted on the subject since the beginning of the twentieth century. In this dissertation, I use social movement theory and a two-tiered empirical approach to examine British slave trade abolition. Systematic qualitative and quantitative analyses of the legislative debates on the slave trade underscores the importance of abolitionists’ rhetorical strategies and the economic utility of Britain’s departure from the trade. A frame analysis of abolitionists’ speeches made during the parliamentary debates suggests that a law to end the slave trade was passed when abolitionist MPs deliberately reframed their ideological campaign to include an increased number of economic pleas in their arguments. Drawing on key aspects of social movement theory, I examine the relationship between resource mobilization, cultural framing and opportunity structures (both political and non-political) and British abolition. My findings suggest that cultural, economic and political factors help to explain why the British slave trade was finally abolished.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.035 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".