Bibliographic record
Abstract
<JATS1:p>“How do I prove I’m gay?” This is the central question for many refugee claimants who are claiming asylum on the basis of sexual orientation persecution. But what are the inherent challenges in obtaining this proof? How is the system that assesses this predicated upon homonormative frameworks and nervous borders? What is the impact of gender, race and class? What is an ‘authentic’ sexual or gender identity and how can it be performed?</JATS1:p> <JATS1:p>Real Queer? is an ethnographic examination of the Canadian refugee apparatus analysing the social, cultural, political and affective dimensions of a legal and bureaucratic process predicated on separating the ‘authentic’ from the ‘bogus’ LGBT refugee. Through interviews, conversations and participant observation with various participants ranging from refugee claimants to their lawyers, Refugee Protection Division staff and local support group workers, it reveals the ways in which sexuality simultaneously disrupts and is folded into the nation-state’s dynamic modes of gate-keeping, citizenship and identity-making, and the uneven effects of these discourses and practices on this category of transnational migrants.</JATS1:p>
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.138 | 0.046 |
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".