Can "slacktivism" work? Perceived power differences moderate the relationship between social media activism and collective action intentions through positive affect
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We argue that the often-used critique of social media activism as merely a ‘feel-good’ mechanism can be countered by conceptualizing social media activism as a necessary type of collective action (i.e., consensus mobilization), incorporating theory on the benefits of positive feelings for activism, and by examining how power may affect these relationships. Women from two different samples (MTurk and university) were randomly assigned to recall a high- versus low-power experience, view real-world events of sexism, and then complete questionnaires assessing endorsement of social media activism, positive affect, and collective action intentions. A dual moderated mediation analyses at the second stage of mediation showed equivalency across two samples, at which point the single moderated mediation model was tested on the combined sample. The model was significant, such that among those in the high-power condition, endorsing social media activism was associated with greater positive affect, which in turn predicted greater collective action intentions. Among those in the low-power condition, however, this indirect effect was not significant. This study provides counter-evidence to the ‘slacktivism’ critique, contributes to theories of collective action, power and their integration, and identifies a possible intervention to enhance the effectiveness of social media activism.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 it