Measuring Identity From an Eriksonian Perspective: Two Sides of the Same Coin?
Bibliographic record
Abstract
In this article, we report the results of 3 studies evaluating the psychometric properties of scores generated using the Erikson Psychosocial Stage Inventory (EPSI; Rosenthal, Gurney, & Moore, 1981 Rosenthal, D. A., Gurney, R. M. and Moore, S. M. 1981. From trust to intimacy: A new inventory for examining Erikson's stages of psychosocial development. Journal of Youth and Adolescence, 10: 525–537. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) with emerging adults. In Study 1, a hybrid bifactor solution, consisting of an overall identity factor as well as of “method effects” factors for identity synthesis and identity confusion, provided a better fit to the data than did either one or two-factor solutions. This bifactor solution was largely invariant across gender and across Whites, Blacks, and Hispanics. In Study 2, the overall identity, identity synthesis, and identity confusion scores were shown to possess convergent validity with another Eriksonian measure and with measures of identity status. In Study 3, the EPSI subscale scores were shown to possess construct validity vis-à-vis self-esteem, purpose in life, internal locus of control, ego strength, anxiety, and depression. We discuss implications for the measurement of identity.
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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 | 0.042 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.009 | 0.018 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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 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".