Bibliographic record
Abstract
Bill O’Grady is a Professor in Sociology. He recently completed a research project in Toronto that examined the enforcement activities of the Ontario Safe Streets Act in relation to homeless youth. Currently, with the John Howard Society of Ontario, he is working on a SSHRC funded project on inmate re-integration in Canada. He is a member of the Canadian Homeless Research Network and an advisory member of Raising the Roof’s Advisory Board of Youth Works. For more information about Bill O’Grady’s research, please go to his website at https://www.uoguelph.ca/socioanthro/bill-ogrady \nTad McIlwraith is an Assistant Professor in Anthropology. His academic work involves the documentation of territoriality and the identification of rights of local Indigenous peoples to use land. These days, this usually means an effort to understand contemporary Indigenous land use in the context of mining and logging. His work includes an effort to understand the attitudes and biases that underpin consulting anthropology projects such as traditional land use and occupancy studies. Currently, he is involved with the Splatsin Nation of the north Okanagan and Shuswap regions of British Columbia on a project related to the challenges they face accessing traditional and current fishing and hunting areas. The barriers they face stem from the processes of colonialism and include private property and fences lines. He is also working with the Splatsin on their response to the possible renewal of the Columbia River Treaty between the United States and Canada. He is helping a Sekani family from north of Prince George, BC on the production of a family history. He is also involved with Tahltan-language speakers (northwestern BC) on language revitalization projects. For more information about Tad McIlwraith’s research, please go to his website at https://www.uoguelph.ca/socioanthro/tad-mcilwraith
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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.066 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".