The positive side of negative affect: Partial support for Identity Theory
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
As per Identity Theory (Burke & Stets, 2009), individuals have a proclivity to reflect about their behaviour and the extent to which it is consistent with their personal identity meanings. As such, self-reflection can yield negative or positive affect. In particular, negative affect serves a motivational function which helps individuals realign their behaviour with their identity meanings. In the exercise domain, no past research nested in Identity Theory has examined the predictive influence of negative affect on motivational and behavioural outcomes across time. This preliminary study aimed at filing this gap. Data was collected at two time points from 129 university students. We conducted hierarchical regressions to examine whether negative affect predicted exercise intentions (frequency and strength), ? in exercise intentions, exercise at time 2, ? in exercise, and perceptions of identity consistency at time 2 (while controlling for exercise identity, identity-consistency judgment, and past exercise). Negative affect was only a significant predictor of exercise intentions (? = .16, p = .041; ?R 2 = .020) and change in exercise intentions (? = .20; p = .041; ?R 2 = .032). Results partially support the motivational function of negative affect within Identity Theory. However, negative affect did not predict exercise at time 2, ? in exercise across time, and identity consistency at time 2. Musings regarding the role and strength of negative reactive responses are presented. Acknowledgments: Funding from the Social Sciences and Humanities Research Council (SSHRC) is gratefully acknowledged.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it