Reconnecting and Reconstructing: Taking Stock of the STLHE 2022 conference
Bibliographic record
Abstract
Academic conferences are key spaces of knowledge sharing and professional development. As a national society which has pledged to undergo “a robust examination of its attention to equity, diversity, and inclusion throughout the organization” (STLHE/SAPES 2021), we undertook an evaluation of the diversity of participants and presentation topics at the 2022 conference. This paper reports on some of the distinctive aspects of the 2022 conference as well as the findings of the evaluation such as diversity of participants by gender and ethnic identity, province, institution type, discipline, and more. While the 2022 conference was unique in many ways due to being STLHE’s first face-to-face conference since 2019, this report provides a useful baseline with which to compare the diversity of participants and presentation topics in future years. The report concludes with additional recommendations for programming decisions to support and evaluate equity, diversity, and inclusivity at future conferences. Keywords: conference, diversity, participation, presentation topics, Society for Teaching and Learning in Higher Education
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".