Bibliographic record
Abstract
In this article, the author shares her experiences as a doctoral student at the Unsettling Feminism(s) conference in Chicago. She argues that this unconference forced her to question how the academy conceives of “academic conferences” as venues of student–professional development. From the perspective of a racialized woman, an immigrant, a scholar, and a person with a disability, such professional gatherings that honor social workers’ and researchers’ multiple identities and offer valued spaces for marginalized stories to be told and heard can be personally and professionally transformative. The author uses the metaphor of an elephant in the room to argue that even though it may be unsettling, the academy must be willing to risk uncomfortable dialogues to advance social work education, practice, and research and to enhance students’ intellectual creativity.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.062 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".