Bibliographic record
Abstract
N either of us had any sustained encounter with Hamilton or its harbour until 1993, the year that we both joined the community of scholars at McMaster University.A few years later, we were asked to do a little historical research for Ecowise, a project focused on the Hamilton Harbour Remedial Action Plan.We thank the biologists, economists, political scientists, psychologists, and other researchers in the project -and most particularly Mark Sproule-Jones -for welcoming us to their group, which had received funding from Canada's three research councils.We also thank the many members of the Bay Area Restoration Council and Bay Area Implementation Team -and most particularly John Hall -for making us feel that we had something to contribute to their valuable work.Our initial research led to an invitation to curate an exhibition at what was then a new and innovative type of museum in Hamilton, the Workers Arts and Heritage Centre.Mary Breen, Craig Heron, Franca Iacovetta, and Renee Wetselaar encouraged us to undertake an exhibit and generously tolerated two novice curators working at the centre.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.373 | 0.306 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".