Bibliographic record
Abstract
This paper uses framing theory to challenge previous understandings of queer safe space, their construction, and fundamental logics. Safe space is usually apprehended as a protected and inclusive place, where one can express one’s identity freely and comfortably. Focusing on the Jerusalem Open House, a community center for LGBT individuals in Jerusalem, I investigate the spatial politics of safe space. Introducing the contested space of Jerusalem, I analyze five framings of safe space, outlining diverse and oppositional components producing this negotiable construct. The argument is twofold: First, I aim to explicate five different frames for the creation of safe space. The frames are: fortification of the queer space, preserving participants’ anonymity, creating an inclusive space, creating a space of separation for distinct identity groups, and controlling unpredictable influences on the participants in the space. Second, by unraveling the basic reasoning for each frame and its related affects I show how all five frames are anchored in liberal logics and reflect specific ways in which we comprehend how queer subjectivities produce/are produced through safe space and its discourse.
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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.062 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".