Bibliographic record
Abstract
Over the last decade, public discourse in Europe and North America has beenoverwhelmingly in favor of banning the face veil (niqab). Politicians like JackStraw in the UK or John Charest in Québec have commented on its putativehindrance to community integration due to its covering of the face. So a bookentitled Face Politics would seem to offer some insights into this anti-niqabdynamic. A quick perusal of the index for “niqab,” “Islam,” and “Muslimwomen,” however, comes up unexpectedly empty. What, then, is “face politics” and how can an academic discussion about the “face” not mention niqab, arguablyone of the most burning issues of “face politics” this century?The book is a profound, intellectually challenging, sometimes dense, andyet empathetic and beautifully written exploration of how contemporary westernpolitics is predicated around individuality and the separatedness of being,signified by the idea of the face as a “window onto the [individual’s] soul” (p.165). Because she believes that “a politics that makes the face is a politics thatproduces the person as an object” (p.7), the author wishes to propose a differentconcept of the face, that of a mask hiding our inseparable connectedness, andconcludes that such an alternative would lead to a profoundly different, andbetter, political society, one symbolized by the concept of the tango. Indeed,the tagline on the dedication page is “If the face is a politics, dismantling theface is also a politics,” from French philosopher Gilles Deleuze and psychoanalystFélix Guattari’s 1980 book A Thousand Plateaus: Capitalism andSchizophrenia ...
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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 | 0.003 |
| 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 | 0.006 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.124 | 0.043 |
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".