The limits of literature as liberation: Colonialism, governmentality, and the humanist subject
Bibliographic record
Abstract
Scholars in both the humanities and management remain attached to the idea that literature will set us free. Whether this is because literary text seems unconstrained by our epistemes or reading literature offers a practice through which we will be able to shape ourselves into the people we want to be, many of us understand literature as something that offers us a chance to emancipate ourselves from the regime of knowledge we have now. Nevertheless, as the history of literature as colonial governmentality suggests, literature and literary study have been crucial forms of knowledge-power for creating and maintaining organizational structures as well as producing the willing subjects that make those structures work. This being so, how is it that are we still interested in using literature to make “better” people, whether the people in question are ”better” managers or their subordinates, rather than reorganizing literary study in the contemporary university?
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.118 |
| Scholarly communication | 0.024 | 0.019 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| 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".