The association between political identity centrality and cancelling proclivity
Bibliographic record
Abstract
Augmented by the rise of social media, contemporary culture has increasingly witnessed the phenomenon of "cancellation" - that is, a brand's swift and public fall from grace, catalyzed through digital platforms like Twitter and, in turn, traditional media. We are the first to examine individual difference predictors of cancelling proclivity. We explore the relationship between a novel individual difference, political identity centrality (the extent to which one's political identity [e.g., liberal, conservative] is central to self-concept), and individuals' propensity to seek retribution from a moral transgressor online (i.e., their "cancelling proclivity"). Additionally, we test the mediating roles of individual differences in moral exporting (actively promoting and supporting the proliferation of one's own moral beliefs), social vigilantism (the tendency of individuals to impress and propagate their "superior" beliefs onto "ignorant" others), virtue signaling (signaling one's virtuousness for public respect or admiration), and self-efficacy on the relationship between political identity centrality and cancelling proclivity. Using an online panel (n = 459), we uncover that political identity centrality is significantly and positively associated with cancelling proclivity operationalized as reaction strength to transgressions and calling-out (calling attention to a transgression) and piling-on a transgressor (mass public prolific addition of comments about the transgression and transgressor). Interestingly while both virtue signaling and social vigilantism were found to be significant mediators, they played distinct roles wherein virtue signaling mediates the relationship for strength of reaction to transgressions, and social vigilantism mediates the relationship for calling-out and piling-on. The current research illustrates that some individual behavior may be less about what someone believes and rather the importance of those beliefs to one's identity - a valuable insight not previously identified in the literature. We discuss theoretical contributions, implications for future research, and applied implications (e.g., how brands might recover from cancellations).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".