Bibliographic record
Abstract
I came to theory because I was hurting -the pain within me was so intense that I could not go on living.I came to theory desperate, wanting to comprehend -to grasp what was happening around and within me.Most importantly, I wanted to make the hurt go away.I saw in theory then a location for healing. -bell hooks, Teaching to Transgress: Education as the Practice of FreedomThe subject of this book is identity/difference politics, both in terms of how it is studied and how it shapes actual socio-political relations.I offer a theory and practice that is based on analyzing and critiquing how and with what effects power shapes difference.Theoretically and politically, I take as my point of departure the liberal multicultural approach.My journey with liberal multiculturalism began when my family and I emigrated from London, UK, to Canada.We did not come to Canada until the early 1990s, but the idea of doing so was planted much earlier.It had its roots in the capillaries of colonialism that had first led my parents to move from Punjab, India, to the UK, and then again, farther west to Canada.This colonial imaginary was and continues to be steeped in a legacy of British colonialism in India, as well as in acts of resistance practised by my great-grandparents and grandparents against British rule in India.More directly, the prospects of immigrating to Canada were motivated by the overt racism we experienced in London.Several members of my immediate and extended family had been physically attacked there on racial grounds, some of them more than once; at university I watched white professors regularly give preference to white students; as Asians, my sisters and I were very aware of where we were safer and where we were not, and of the x
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.528 | 0.351 |
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".