On the Risks of Recycling Because of Guilt: An Examination of the Consequences of Introjection<sup>1</sup>
Bibliographic record
Abstract
The present study sought to examine the influence of introjected beliefs on individuals’ vulnerability to counterattitudinal arguments. University students’ reasons for engaging in proenvironmental behaviors were assessed prior to their reading excerpts from a counterattitudinal article. The excerpts were written by a personally attractive or unattractive author and contained either weak or strong arguments against recycling. Our results show that individuals who were highly introjected about recycling (e.g., “I recycle because I would feel guilty if I didn't”) were influenced by the personal attractiveness of the source but not by the strength of the specific arguments. Specifically, a thought‐listing procedure revealed that introjection was associated with generating more favorable thoughts and fewer counterarguments about the anti‐recycling message when the author was personally attractive than when he was unattractive.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".