Bibliographic record
Abstract
The many usages of the term ‘secularism’ have generated an ambiguity in the word; as a political guise, it may be used to engender anti-religious fervor. Particularly in regards to veiling among female Muslim adherents, the attainment of a secular state and touting of the necessity of dismantling religious symbols have functioned as linguistic shields. By calling a “burka ban” necessary or even egalitarian secularization, legislators employ ‘secularization’ as jargon for political ends, enacting a stance of supremacy under the semblance of progress. Secularization has come to function as a political tool - in the name of it, governments may prescribe which cultural symbols are normative and which are of ‘other’ cultures or religious origins. As such, the identification of some religious symbols as foreign and others as normative is a usage of secularization for normalization of dominant religious expression. In this, there is an implicit neocolonialism; by imposing standards of cultural normalcy which are definitively nonMuslim, such policies attempt to divorce Muslims from Islam. Further, I intend to investigate the gendered aspect of secularization politics. By critiquing clothing and body policing of women, I will demonstrate how secularization projects use the female body and dress as a site for display. By rendering the female physically emblematic of the honor and virtue of an ‘other’ culture, those enacting secularization norms target women’s bodies to act as visual exhibitions of the dominant culture’s hegemony. Here, we see gendered secularization at work - female bodies become controlled by the antireligious zeal of the state, while the state carries out this control on the predicate that it is the religious group enacting unjust control. As such, the policing of female Muslim bodies is symbolic of the policing of Islam as a whole; it acts as an illustration of an imposed, gendered secularization project.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".