Bibliographic record
Abstract
This collection challenges misconceptions that rural Canada is a bastion of intolerance. While examining the extent and nature of contemporary cultural and religious discrimination in rural Canadian communities, the editors and contributors explore the many efforts by rural citizens, community groups, and municipalities to counter intolerance, build inclusive communities, and become better neighbours. Throughout, scholars and community leaders focus on building new understandings, language, and ways of thinking about diversity and inclusion that will resonate with rural people. Scholars of rural studies will find this book useful as will rural community leaders and community organizers. \n \nContributors: Clark Banack, Ray Bollman, Claudine Bonner, Corina Borri-Anadon, Jen Budney, Michael Corbett, Roger Epp, Murray Fulton, Stacey Haugen, Phil Henderson, Sivane Hirsch, Michelle Lam, Coleen Lynch, Aasa Marshall, Darcy Overland, Trista Pewapisconias, Dionne Pohler, Samuel Reimer, Jennifer Tinkham, Kyle White
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".