Bibliographic record
Abstract
The creation of a digital exhibit ends in a final product, but there are many more outcomes than what can be seen by simply experiencing the exhibit. The work that goes on between group members and their partners is often overlooked, but is sometimes the most important outcome of a project for those who were a part of it. The project that resulted in the exhibit: Fight, Fight, Fight! Anti-authoritarianism in second-wave feminist movements in Edmonton, Alberta as reflected in artifacts from the Karen Rowswell collection at the City of Edmonton Archives, was undertaken by three students for the course GSJ (Gender and Social Justice) 598/DH (Digital Humanities) 530 taught by Professor Deb Verhoeven. A subset of the project group collaborated on the Forum For Information Professionals (FIP) Conference presentation. We found that besides the exhibit itself, the results of this project were also found in the relationships and processes that we built. The digital exhibit can be viewed here: https://omekaprojects.artsrn.ualberta.ca/coea_ms-1210karenrowswell/s/FeminismAndAuthority.
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 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.073 | 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".