Identity Processing and Personal Wisdom: An Information-Oriented Identity Style Predicts Self-Actualization and Self-Transcendence
Bibliographic record
Abstract
This study was designed to investigate whether individual differences in young adults' identity processing styles predict aspects of personal wisdom (self-actualization and self-transcendence) and related outcomes (meaning in life and subjective happiness). Fifty-three men and 105 women completed self-report questionnaires measuring: identity commitment; identity processing styles (informational, normative, diffuse-avoidant); self-actualization (via autonomy, adaptation, and psychological functioning); self-transcendence (decreasing reliance on externals for self-definition, increasing interiority, and spirituality); meaning in life; and subjective happiness. Both identity commitment and an informational identity style were positively correlated with self-actualization and self-transcendence. When levels of identity commitment were controlled via hierarchical regression, self-actualization and self-transcendence were positively predicted by the informational identity style. Structural equation modeling further revealed that the use of an informational style positively predicts self-actualization and self-transcendence, which in turn positively predicts the presence of meaning and subjective happiness. This path model was not found for either the normative or diffuse-avoidant identity styles.
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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".