Bibliographic record
Abstract
INTRODUCTION PART ONE: TRACKING THE TRUTH: THE LITERATURE OF EXPOSURE 1. The Case of the Disappearing Women (Vancouver Sun, 2001) 2. Reinventing our Wheels (Ottawa Citizen/Vancouver Sun, 2001) 3. Death Wish: Humans and the Planet (Globe and Mail, 2001) 4. Asbestos, Again (Toronto Star, 2003) 5. Criminalizing Dissent (Ottawa Citizen and Southam News, 2001) 6. Dialling for Dollars (Toronto Star, 2002) 7. Tarnishing the Ivory Tower (Globe and Mail, 2001) 8. Blind Faith (Hamilton Spectator, 2005) PART TWO: DOCUMENTING THE TRUTH: COMPUTER ASSISTED REPORTING 9. Nowhere to Go (Toronto Star, 2001) 10. Nobody's Children (Toronto Star, 2001) 11. Recipe for disaster (Hamilton Spectator, 2001) 12. Drive Clean: Smokescreen (Hamilton Spectator, 2004) 13. Singled Out: Racial Profiling (Toronto Star, 2002) PART THREE: TALKING INVESTIGATIVE JOURNALISM 14. Conversations with Canadian journalists 15. Conclusions APPENDICES REFERENCES INDEX
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.024 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".