Bibliographic record
Abstract
To say that Canada is a society of diversities and difference is surely an understatement.Canada represents an extremely diverse society in terms of new Canadians and racialized minorities, including over two hundred different ethnic groups, as well as some eighty distinct Aboriginal nations.In addition to its racial, ethnic, and Aboriginal differences, Canada is home to class diversities, ranging from ruling to working to underclass; diversities in gender, including the transgendered and intersexed; and diversities associated with religion, sexual orientation, and age.Difference is no less prevalent a reality.In contrast to the descriptive terms "diversities" and "differences, " both of which denote human variation along physical, cultural, social, and psychological lines, references to "difference" connote a more politicized concept that contextualizes diversities within a contested framework of inequality and power.To the extent that mainstream media have proven diversity-friendly by embracing superficial differences yet difference-aversive in rejecting deep differences and politicized diversities, the distinction is critical.The profusion of diversities and difference in Canada cannot be denied.Expressions of politicized diversities (i.e., difference) include, among others, the politics of aboriginality, the proliferation of identity politics around race or gender, and the politicization of sexuality in claiming public space.Nor should we refute the reality of both government and institutional initiatives for accommodating diversities and difference.On one side are equity-based initiatives for levelling the playing field, including those under the Employment
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.516 | 0.303 |
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".