Disciplining Race: Crossing Intellectual Borders in African American and Postcolonial Studies
Bibliographic record
Abstract
One of the common conceits of intellectual work, particularly in postcolonial theory, is that it is cosmopolitan in nature. Postcolonial critic Edward Said has made a virtue of the intellectual who crosses political and cultural boundaries.1 Julia Kristeva has theorized cosmopolitanism as a political and intellectual position in Nations Without Nationalism. In my own research into the recent development of the field of Postcolonial Studies, however, I have found that political borders have been quite effective in reducing intellectual exchanges between individuals working, nominally, on the same topic. In this paper, I will argue that the US–Canadian border exists not only along the 49th Parallel but also extends its reach across academic fields of inquiry—specifically, this paper will be looking to the divisions and potential intersections between Postcolonial and African American Studies.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.032 | 0.066 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".