Bibliographic record
Abstract
Anderson, Mark Cronlund and Carmen L. Robertson. Seeing Red: A History of Natives in Canadian Newspapers. Winnipeg: University of Manitoba Press, 2011. 336 pp. $27.95. The importance of this study, and those which hopefully will follow, came home to hit hard while I was watching an episode of the classic television western, Wagon Train. Oh, yes, I was well aware of the facts that aboriginals have not fared overly well in the media culture of this country and any one of a dozen others around the globe. And I cannot comprehend the image of a native warrior holding a piece of female underwear as his colleagues attack the train. The show was not, however, a matter of degrading a specific group of people. It was a statement on race relations created about seven decades ago. As the authors point out in the first chapter, no one placed the question of land use or land space on the agenda when the Canadian government purchased the holdings of the Hudson's Bay Company in 1869 to form what eventually became the provinces of Alberta and Saskatchewan and the expansion of Manitoba. The book contains twelve chapters and a summary conclusion which covers considerable territory. Although it is not within the final chapter, the study effectively concludes with a serious look at one of the major native uprisings in Canada in a small Quebec town, Oka, which is famous for its cheeses. In that case, the town council had proposed building a golf course on lands which the local native community had defined as theirs. Eventually, the natives blockaded a road, which led to a violent confrontation with the provincial police, who lost one of their officers in the conflict. In many ways, Oka represented the turning point in native and non-native affairs. More serious confrontations were to follow. In particular, a conflict in Ontario at a provincial park, which local natives argued was the site of a burial ground. The government disagreed and sent in the Ontario Provincial Police to remove the natives from the site. When the dust cleared, one of the native protesters was dead. So, how does the press fit into all ofthisi For the answer we return to Wagon Train and the attitudes that are encompassed, which the authors argue are still plaguing native communities today. I can attest personally to the difficulty of working with newspapers whose content is seldom indexed. It presents a challenge to cover what is considered to be important to the story and, of course, that leads one to wonder why a significant event escapes attention. Quite simply, there is just not enough space to be that thorough. …
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.014 | 0.027 |
| Science and technology studies | 0.025 | 0.008 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".