The political solidarity measure: development and validation in University student samples
Bibliographic record
Abstract
Political solidarity is often key to addressing societal inequities and injustice (Mallett, Huntsinger, Sinclair, & Swim, 2008; Scholz, 2009). Yet social psychology is without a common definition or comprehensive measure of this construct, complicating advancements in this burgeoning field. To address these gaps, across five computer-based studies of Canadian university student samples, I created and validated the Political Solidarity Measure (PSM). I conceptualized political solidarity as consisting of three factors: allyship with a disadvantaged outgroup, a connection to their cause, and a commitment to working with them to achieve social change. In Study 1, 1,594 participants completed the initial 30-item pool. A series of exploratory factor analyses, along with indices of factor retention (e.g., when m = 3, RMSEA.LB < .06, AIC Δi < 1), supported the three-factor model. I retained three items per factor to create the 9-item PSM used in subsequent studies. Confirming this factor structure, a three-factor model adequately fit data collected for Study 2 (N = 273; Robust RMSEA = 08; Robust CFI = .97); I thus retained the three-factor model. In Study 3 (N = 259), I found evidence of the PSM’s convergent validity (rs > |.19|, ps < .03), discriminant validity (rs < |.10|, ps > .23), and its medium-term (three to six month) retest reliability, r(254) = .62, p < .001. Study 4 (N = 130) also assessed retest reliability, but in the short-term (a three-week period), r(121) = .60, p < .001. Finally, I demonstrate the PSM’s predictive validity in Study 5 (N = 221). Controlling for modern racism, PSM scores predicted collective action intentions and behavior benefitting the outgroup: Participants who reported higher political solidarity donated more to the outgroup’s cause, β = .25, t(215) = 3.21, p = .002, and were more likely to agree to create a message of support, than not agree, b(SE) = 1.09 (0.27), p < .001, OR = 2.98, 95% CI [1.76, 5.05]. The PSM will enable measurement of political solidarity across issues and time, facilitate comparisons of interventions to shift political solidarity, and add to knowledge of intergroup relations and social change.
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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 | 0.028 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".