Learning to leave liberalism…and live with complicity, conundrum and moral chagrin
Bibliographic record
Abstract
This paper is a story of personal learning. I locate its beginning in my early, comfortable adoption of liberalism as the preferred perspective for my work as a philosopher of education. I then trace how and why I became disaffected with this perspective. I describe how learning from students, feminism and critical race theory led to an acceptance of the fact that my particular social locations as a white, upper-middle-class, educated, heterosexual man are not politically neutral as liberalism would have it, but aspects of social relations that are oppressive to others. I illustrate how this development and its implications took shape in my work, leading me to the unpleasant implications of my unavoidable complicity in these relations, even down to the level of my very subjectivity. I worry, then, about an apparent conundrum that ‘I’ experience when I address the question of how ameliorative change might be initiated, and end with some injunctions to myself.
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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.014 | 0.085 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".