Seeing failure in your life: Imagery perspective determines whether self-esteem shapes reactions to recalled and imagined failure.
Bibliographic record
Abstract
The present research reveals that when it comes to recalling and imagining failure in one's life, changing how one looks at the event can change its impact on well-being; however, the nature of the effect depends on an aspect of one's self-concept, namely, self-esteem. Five studies measured or manipulated the visual perspective (internal first-person vs. external third-person) individuals used to mentally image recalled or imagined personal failures. It has been proposed that imagery perspective determines whether people's reactions to an event are shaped bottom-up by concrete features of the event (first-person) or top-down by their self-concept (third-person; L. K. Libby & R. P. Eibach, 2011b). Evidence suggests that differences in the self-concepts of individuals with low and high self-esteem (LSEs and HSEs) are responsible for self-esteem differences in reaction to failure, leading LSEs to have more negative thoughts and feelings about themselves (e.g., M. H. Kernis, J. Brockner, & B. S. Frankel, 1989). Thus, the authors predicted, and found, that low self-esteem was associated with greater overgeneralization--operationalized as negativity in accessible self-knowledge and feelings of shame--only when participants had pictured failure from the third-person perspective and not from the first-person. Further, picturing failure from the third-person, rather than first-person, perspective, increased shame and the negativity of accessible knowledge among LSEs, whereas it decreased shame among HSEs. Results help to distinguish between different theoretical accounts of how imagery perspective functions and have implications for the study of top-down and bottom-up influences on self-judgment and emotion, as well as for the role of perspective and abstraction in coping.
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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 | 0.001 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".