Expanding Social Justice: Exploring Connections Between Immigration and Indigeneity
Bibliographic record
Abstract
Most discussions of group--‐differentiated disadvantage seek to explain its covert and overt nature through the experiences of dominant groups and their relations to subordinate groups. This is a vertical approach to social injustice. Instead of taking this approach, I take a horizontal approach that seeks to determine whether there are logics that produce disadvantage that are invisible to the vertical understandings of socially constructed group--‐ differentiated disadvantage. To this end, I critically consider the relationships between disadvantaged groups by reflecting on the experiences of Black Canadians and Canadian Aboriginals. Their experiences reveal the underbelly of Canadian multiculturalism and of discourses of membership and belonging. I explore the ways in which these groups have potentially complex and conflicting modes of injustice that elicit potentially conflicting and complex prescriptions. Recognizing this has the potential to facilitate a finer--‐grained sensitivity to the description and potential amelioration of group--‐differentiated disadvantage and to problematize discourses of membership and belonging in their instantiation in current Canadian practices, norms, and governing arrangements.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.029 | 0.064 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".