New Directions in the Controversial Study of Self-esteem: A Review with Suggestions for Future Research
Bibliographic record
Abstract
The construct of self-esteem (SE) is controversial due to conceptual and methodological problems that have led to the near abandonment of its study. While little is known about the theoretical underpinnings of SE and its functions, clinicians, educators, organizational leaders, and policy-makers dangerously push for SE programs in hopes of boosting performance. Attempting to boost performance using unsubstantiated praise as a motivator may actually contribute to egotistical and narcissistic attitudes and related behaviours, yet good performances tend to raise self-ratings of SE.There are still good reasons to study SE because evidence supports positive relationships between SE and happiness, SE and well-being, as well as low SE and anxiety, rumination, depression, and poor self-regulation. Self-evaluation and self-regulation are strongly related to both SE and the cognitive phenomenon of inner speech (IS), and both SE and IS are strongly influenced by individual and contextual differences. Therefore, I use the present review to theorize about functions of SE within a self-system, place the study within current paradigms considering both psychological and social influences, and offer suggestions for future research in fundamental SE phenomenology using IS sampling.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".