Bibliographic record
Abstract
Bien que l'accès efficace et adéquat demeure un but commun pour la plupart des institutions d'archives, il n'est que rarement atteint complètement.Cet article se penche sur des obstacles spécifiques qui empêchent l'accès aux utilisateurs transgenres et aux documents transgenres dans les archives.L'article affirme que l'en vironnement et l'usage de la langue influencent les façons dont les utilisateurs appro chent les archives et les documents qui y sont conservés.Plutôt que de promouvoir un accès adéquat, l'article suggère que la satisfaction reportée ou refusée peut aussi produire des expériences enrichissantes pour les chercheurs aux archives.ABSTRACT While efficient and satisfactory access may be a common goal for most archives, it is rarely achieved in full.In this article, the author considers specific access barriers for both transgender patrons and transgender materials within archives.In particular, the author argues that environment and language shape the ways in which patrons encounter archives and the materials contained therein.Rather than seeking satisfactory access, the author suggests that deferred or denied satisfac tion might also produce productive encounters for archival researchers.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.005 |
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".