Bibliographic record
Abstract
While many have investigated media constructions of ‘newsworthy’ and ‘non-newsworthy’ crimes and their victims, the overwhelming focus of these analyses has been upon violent crime in its myriad forms. In contrast, this article examines the Canadian print media’s peculiar construction of crime, criminals, and victims in the world of art fraud from 1978 to 2012. Just as art fraud is not thought of as normal ‘crime news’ and is bracketed away elsewhere, the victims of art fraud tend not to be regarded as ideal victims. We note that allegations of art fraud in Australia and elsewhere have occasionally provided a catalytic environment for discussions of ‘who is an “Aboriginal artist”?’, ‘what is “Aboriginal art”?’, and ‘who owns Native culture?’ However, the Canadian print media’s response to allegations of fraud in relation to the art and artistry of Canada’s indigenous peoples suggests how contemplation of these questions can be forestalled.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.057 |
| Scholarly communication | 0.021 | 0.031 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".