Racial Origins of Civic Nationalisms: Exploring Race Creation in Australia and Canada
Bibliographic record
Abstract
Nationalism is an ideology. It claims to know when a nation exists, who belongs to it, and who does not, and why. It advocates the creation of an individual state as a nation's natural right, a precondition for realization of its fullest potential. Nationalism invents a group of people who recog-nize in each other a shared community of culture, history, and future expectation. (Senese, 2000) Nationalism in any guise creates confusion, not clarity; anx-iety, not tranquility. (Senese, 2000, 125) The quotations above demonstrate the complexity of nationalism. In her essay entitled, "Weeds in the Garden of Civic Nationalism", Senese (2000) considers the major 'weed in the garden ' of Canadian civic nationalism to be the ethnic nationalism of French Canadians (113). However, her discussion of civic nationalism is incomplete. In identify-ing who belongs to the nation, she fails to notice the exclusion of "the other " that inhabits the same territory as English and French Canadians and their civic or ethnic nationalisms: Aboriginal peoples and "race" minorities. As a result, this omission demands greater exploration. The history of Aboriginal oppression and colonization in settler societies and their future nation-states is relatively well known and documented
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".