Solidarity Not Homogeneity: Constructing a Superordinate Aboriginal Identity That Protects Subgroup Identities
Bibliographic record
Abstract
Superordinate identities formed around shared oppression provide political and psychological resources for marginalized groups. However, superordinate identities can also threaten the identities of the subgroups they attempt to bring together. We examined how a superordinate identity was constructed to protect subgroup identities using data from 31 urban Aboriginal participants who strongly identified with both their subgroup (heritage cultures) and superordinate Aboriginal identities. Participants defined the superordinate Aboriginal identity as a fundamentally diverse category where no one subgroup was more representative of the wider category than others. Participants also put their respect for subgroup diversity into practice by regularly engaging with Aboriginal (subgroup) cultures other than their own. Finally, participants felt that representations of the superordinate Aboriginal category should prioritize local cultures. We discuss these findings in relation to research in social psychology on superordinate and subgroup identities, multiculturalism, and collective resistance and provide some suggestions for how this work may be extended.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".