Not All Promotion Is Good Promotion: The Pitfalls of Overexaggerated Claims and Controlling Language in Exercise Messaging
Bibliographic record
Abstract
Across 2 studies, the authors explored reactance effects to overexaggerated claims and controlling language in exercise messaging. In Study 1, participants received either a message exaggerating the benefits of an upcoming exercise session or no message. They subsequently undertook a mundane exercise session led by an instructor, which was either need supportive or "realistically controlling." Relative to no-message participants, those who had read the message reported less positive evaluations of the session. These results were observed despite participants in the message condition holding more positive presession expectations, and the effect was apparent even for those who received need-supportive instruction. In Study 2, participants read an advertisement that was written in either autonomy-supportive language or controlling language. Despite reporting comparable expectations, participants who received a controlling-language message reported significantly greater anger and freedom threat-factors commonly linked to contrast effects. These studies highlight the operation of message-driven contrast effects in exercise.
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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 | 0.045 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".