Bibliographic record
Abstract
Preliminary research, carried out exclusively on the World Wide Web (the Web) for an expression of Interest proposal to Canadian Heritage last year, raised a serious question about the breadth, depth and quality of existing resources on the ethnocultural diversity and history of Canada's peoples on the Internet.! Among the groups explored were the Italian-Canadians.This paper will provide a brief summary of the findings based on that research, as well as additional investigations on the Italian Canadian presence on the Internet.Its purpose is to lay the groundwork for more exhaustive and comprehensive analyses of the possibilities inherent in the Web to create, reflect or distort the story of any (ethnocultural) group.Given that the Internet is fast becoming a significant source of information, in particular among millennials,?it is vitally important that we be aware of what currently exists about Italian Canadians in the 'google' universe, to take stock of the perspectives portrayed, and to find ways to augment those resources.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".