Bibliographic record
Abstract
In Tropical Freedom Ikuko Asaka engages in a hemispheric examination of the intersection of emancipation and settler colonialism in North America. Asaka shows how from the late eighteenth century through Reconstruction, emancipation efforts in the United States and present-day Canada were accompanied by attempts to relocate freed blacks to tropical regions, as black bodies were deemed to be more physiologically compatible with tropical climates. This logic conceived of freedom as a racially segregated condition based upon geography and climate. Regardless of whether freed people became tenant farmers in Sierra Leone or plantation laborers throughout the Caribbean, their relocation would provide whites with a monopoly over the benefits of settling indigenous land in temperate zones throughout North America. At the same time, black activists and intellectuals contested these geographic-based controls by developing alternative discourses on race and the environment. By tracing these negotiations of the transnational racialization of freedom, Asaka demonstrates the importance of considering settler colonialism and black freedom together while complicating the prevailing frames through which the intertwined histories of British and U.S. emancipation and colonialism have been understood.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.088 | 0.014 |
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".