Bibliographic record
Abstract
Another university is possible! An exclamation point. A claim. A theme. The title of the 2024 ESJP conference. Do it differently! A call to reimagine conference engagements and practices. During the conference, I listened to colleagues presenting their work. Some presentations. But also workshops. An attempt to do academia differently. Another academia. Some of it different. More play. Less performance. More activity. Less lecturing. More colorful wax pastels and playdough. Less black words on white paper and screens. Some of it giving hope. Inspiring. Some of it challenging academic rules. Some of it playing academic tunes. Using academia’s colors. Performing academic performances. Puzzling. Why is it so hard to do it differently? Even if the invitation is to do it differently. Think. Feel. Believe. Another university possible? Another engineering possible? Maybe. But why hasn’t this been easier? Possible, so far? bell hooks writes, “Dominator culture has tried to keep us all afraid, to make us choose safety instead of risk, sameness instead of diversity. Moving through that fear, finding out what connects us, revelling in our differences; this is the process that brings us closer, that gives us a world of shared values, of meaningful community” (2003, p.197). How can we build these meaningful communities? And can we? This piece unpacks some thoughts on community in conversation. A collective movement from a caricature to regeneration. Updated with minor typographical corrections: June 30, 2025.
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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.019 |
| Scholarly communication | 0.022 | 0.036 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.008 | 0.019 |
| Insufficient payload (model declined to judge) | 0.050 | 0.031 |
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".