Positive and Negative Self-Worth Beliefs and Evaluative Standards
Bibliographic record
Abstract
This study examined several different types of self-worth beliefs and evaluations as predictors of depression and self-esteem. Based upon a self-schema model of emotion, some of these beliefs and evaluations had a traditional negative focus (e.g., “I am failing at work”), whereas others focused specifically on positive aspects of self-worth (e.g., “I am able to give, as well as receive, in relationships”). Findings indicated that positive self-worth evaluations were one of the main predictors of greater self-esteem and less depression, thus indicating a need for further exploration of the role of positive evaluative components of the self-schema on psychological well-being. Our findings also revealed that self-worth beliefs and evaluative standards pertaining to independence and a sense of mastery over one’s environment were generally better predictors of well-being than those pertaining to relationships with others. This pattern was particularly evident for self-esteem, and supports the distinction made in the self-schema model between self-worth based upon individualism versus relatedness themes. Finally, we compared the relative predictive utility of the self-schema model with a self-worth contingency model advanced by Crocker. Here, the beliefs and evaluations specified in the self-schema model were significant predictors of well-being, above and beyond the specific content domains specified in the self-worth contingency model.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".