It was(n’t) me: Exercising restraint when choices appear self-diagnostic.
Bibliographic record
Abstract
This research tests the hypothesis that individuals exercise restraint for actions that reflect on their self-concept (i.e., self-diagnostic actions). Experiments 1 and 2 show an action framed as occurring at the beginning or end (vs. middle) of a constructed sequence is seen as more self-diagnostic. Accordingly, Experiment 3 finds more restraint in snack choices at the framed beginning or end (vs. middle). Furthermore, the degree of importance of a goal-which reflects its centrality to the self-concept-determines responses to self-diagnosticity cues such as framed positions. Specifically, participants committed to financial goals (Experiment 4) and health goals (Experiment 5) were more likely to make decisions consistent with these goals at the beginning or end, but indulged and splurged in the middle. Experiment 6 shows similar patterns for judgments of magazine subscriptions, but only when individuals are faced with a decision that poses a self-control conflict for them. These results highlight the role of the self in self-control by demonstrating that people exercise restraint when decision contexts seem more telling of the self.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".