With Privilege Comes Responsibility: Why some privileged insiders transform institutions for societal benefit
Bibliographic record
Abstract
Why do some privileged insiders take action to transform institutions for broader societal benefit, while others do not? Privileged insiders are those who, because of their education, socio-economic background, formal position, citizenship, gender and/or race, derive advantages from existing institutional arrangements. While their relative privilege places them in a better position to influence institutions, prior research would suggest that they are unlikely to do so without the prospect of personal gain. We find that privileged insiders feel compelled to engage in prosocial institutional transformation when they situate the problem not with others but with themselves, acknowledging their own complicity in structural injustice. They can navigate the emotional discomfort triggered by moral emotions by taking small pragmatic actions that lower their emotional distress and initiate a cycle of experimentation with change. Finally, we show that the practical evaluative dimension of agency plays a central role in shaping institutional change agency. Foregrounding the role of emotions in practical evaluation, we reveal how transformative templates for action emerge from a deliberative engagement with the self.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".