Exploring the Role of Collective Narcissism and Ideology in Support for Reparations
Bibliographic record
Abstract
Many societies with colonial histories have begun to grapple with their legacy of historical injustices and their ongoing consequences, leading to national apologies and sometimes consideration of reparations. In this context, it is important to understand the factors enhancing or impeding public support for reparations. This dissertation focused on the role of beliefs (ideology) and identity (collective narcissism) as predictors of support for reparations addressing historical injustices. Drawing from existing research, we expected that those higher in conservatism – and those higher in collective narcissism - would oppose reparations more strongly. We also examined the interaction between ideology and collective narcissism, which has not been investigated in past research. Notably, a pilot study preceding the three main dissertation studies revealed a surprising pattern: higher collective narcissism predicted lower reparation support among liberals, but unexpectedly, higher collective narcissism predicted greater reparations support among conservatives. This discovery became the starting point of the dissertation studies aiming to replicate and explain this intriguing finding. In the main dissertation, three studies examined the relation between collective narcissism, political ideology and reparation support in different contexts. Study 1 (N = 785) used a pre-registered correlational design with Canadians examining Indigenous reparations support. Study 2 (N = 245) employed a two-wave design with White Americans examining Black reparations support. Studies 1 and 2 replicated this unexpected interaction across Canadian and American contexts – those who are high in conservatism and collective narcissism reported higher support for reparations, whereas the opposite tendency was observed among liberals. Study 3 (N = 1,047) experimentally tested a possible explanation for the observed pattern in the pilot and Studies 1 and 2. Specifically, we examined whether White conservative collective narcissists might support reparations particularly when it makes their group appear more moral, by framing the leaders of a described reparation effort as either White (ingroup) or Black (outgroup). However, the hypotheses tested in Study 3 were not supported, and this study also failed to detect the originally observed effect, with collective narcissism consistently predicting lower support in both conditions. Therefore, the current dissertation has identified an intriguing and potentially important pattern, but has not yet illuminated the underlying mechanism. These findings challenge existing theoretical understandings of collective narcissism by revealing that collective narcissism's relationship with outgroup attitudes is not uniform but varies systematically with political ideology at least in some contexts. Further, examining patterns another way, we see that traditional ideological divides disappear at high levels of collective narcissism, suggesting that psychological factors related to group identity may be more fundamental than conventional political categories in shaping reconciliation attitudes. The research opens new possibilities for understanding how defensive group identification can facilitate rather than impede support for addressing historical injustices.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".