Canadian Journal of Sociology Online May-June 2004
Bibliographic record
Abstract
This book explores the “intimate intersections and forbidden frontiers ” where race, ethnicity, gender, and sexuality converge. The author defines ethnicity in a broad way to subsume nationalism, race, religious and linguistic groups, while pointing to the historical and contextual fluidity of these terms and, therefore, to their socially constructed character. In a similar social constructionist vein, she defines sexuality as the genitally-based distinction between men and women accompanied by culturally defined appropriate sexual tastes, partners and activities. Nagel wants to understand the social, economic, political, cultural, and / or religious agendas behind difference claims made in social constructions of ethnicity, gender and sexuality. As a result, she proceeds, in eight succinct, cogently argued, and well documented chapters, to map out ethno-sexual constructions; show how hegemonic regimens of sexuality shape ethnic relations, conflicts and boundaries; and document the importance of sexuality in all things racial, ethnic and national. Methodologically, the author chooses examples where ethnicity and sexuality collide in order to expose the often hidden ethnosexual connection. The intent is neither an exhaustive study of locations where race and sex can possibly meet, nor an in-depth analysis of any single era or country or racial or ethnic group. Nagel borrows methodologies and styles of interpretation eclectically from both the
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.281 | 0.064 |
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".