Bibliographic record
Abstract
Queer nightlife is receiving increasing recognition in a growing field of nightlife studies, yet its insights have been largely mined by humanists. In this introduction to a subfield-defining special issue, I blend arguments from the social sciences about “dirty work” with humanistic notions of “disidentification” as a survival strategy to amplify a sociological point of view. What theoretical opportunities arise from working on and against the conservative tendencies of the discipline, neither abandoning queer nightlife for something perceived as more legitimate nor refusing entirely to engage with other sociologists? A review of select multidisciplinary works distills three expressions of disidentification used by researchers to negotiate novel arguments. I describe these as conceptual renovations, deconstructive reframings, and epistemological affirmations. From this baseline, I classify special issue papers into additional clusters that articulate sociology-specific interventions that neither uncritically embrace nor strictly oppose normative standards but transform them from within, what I call reorientations, relational work, and regulated improvisations. These themes together contribute to a knowledge platform about queer nightlife that conveys both shared theoretical frameworks and disciplinary distinctions.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.039 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".