Bibliographic record
Abstract
This article is about the suicide of the chief of police of a small Canadian town, which - according to some - did not actually happen. While employed as a researcher and writer with a museum in Port Moody, British Columbia, the author heard this story as one of many told by the ‘old-timers’ who assisted with the writing of a history book. The controversy over the potential suicide provided the means by which this article reflects on issues of ethics, advocacy, and performance when doing public history. The main request of the old-timers was to ‘put the good stories in’ when writing the book. This expectation caused tension between the author and the museum, reflecting the divide between doing ‘history’ and ‘heritage’. This article draws on Anthropological theories of ‘complicity’ and performance in storytelling to make sense of the author’s role within the context of a museum working to record the stories of long-time residents. The stories of the old-timers were filtered through the lens of early 20th century ideas about gender, race, and class, and affected by a lingering frontier mentality. As such, they wished to see their town’s history told in a very specific way. The story of the police chief’s suicide betrayed this intent, allowing for an analysis of how these expectations can affect the way in which public history is done.
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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".