Bibliographic record
Abstract
ContextAs a queer racialized scholar, I have spent over nine years teaching in academia across various departments and programs, including Conflict Resolution, Sociology, Criminal Justice, Religion and Culture, and Women's and Gender Studies.Although diversity has ostensibly increased in some institutions, the academic landscape remains predominantly white and European-centric.Instructors of color are constantly tokenized as their representation in most departments is still insufficient.Several years ago, a student of mine approached me with excitement, and she said, "When I saw your name on the registrar's site, I wasn't sure how a name like Mehmet could teach Gender and Sexuality, but it turned out to be a great class, thank you!" While the student's intention may have been to express appreciation, the comment was deeply unsettling; it was shocking for me to digest it in many ways.I froze and had an awkward smile on my face until the student left the classroom.However, what I heard from the student did not leave me for so many years, and only now, years later, am I able to write about it.This student (probably like many others) saw my name on the Registrar's website and implicitly assumed that someone with an ethnic(!) name, presumably from a background where gender and sexuality are viewed as troubling, could not possibly be qualified to teach the course.In other words, she only saw my name and appearance attached to my name before I had a chance to stand at the classroom podium and "prove!" myself.I could not help but reflect on Edward Said's (2004) Orientalism and how it "is very much tied to the tumultuous dynamics of contemporary history" (p.870).As Said (2004) succinctly notes, "neither the term Orient nor the concept of the West has any ontological stability; each is made up of human effort, partly affirmation, partly identification of the Other" (p.870).The misrepresented picture of the Other leads to "fear, hatred, disgust, resurgent self-pride and arrogance" (p.870).My
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.076 | 0.032 |
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".