Shared Membership Beyond National Identity: Deservingness and Solidarity in Diverse Societies
Bibliographic record
Abstract
Liberal nationalists argue that identification with the nation promotes feelings of mutual obligation, including support for redistribution. Existing attempts to test this hypothesis have focused on whether the higher sense of national identity among the majority increases support redistribution. We argue for a twofold shift in focus. First, beyond the majority’s own national identity, we need to explore their perceptions of whether minorities share this identity. Second, we need to shift from one-dimensional ideals of ‘identity’ to more complex ideas of attachment and commitment. Do members of the majority view minorities as committed to the nation and willing to make sacrifices for it? Drawing on a custom-designed online survey in Canada, we show that three salient out-groups (Aboriginal peoples, French-speaking Canadians and immigrants) are seen by majority respondents as less committed to Canada, and that this is a powerful predictor of support for general and inclusive redistribution.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".