Measuring selfhood according to self-determination theory: Construction and validation of the Ego Functioning Questionnaire (EFQ)
Bibliographic record
Abstract
The goal of this research was to develop and validate an instrument designed to measure the three types of self proposed by Hodgins and Knee (2002): integrated, ego-invested, and impersonal. This measure was termed The Ego Functioning Questionnaire (EFQ). In Study 1 (N=202), the factorial structure of the EFQ was examined by means of an exploratory factor analysis, and the metric properties of its subscales were documented. In Study 2 (N=300), the 3 factor structure of the EFQ was successfully corroborated using a confirmatory factor analysis. In Study 3 (N=131), associations between the EFQ and a variety of cognitive, affective, and social variables were found to display meaningful patterns, thereby providing support for the EFQ?s construct validity. Also, the EFQ was not susceptible to socially desirable responding. Results are discussed in terms of their fundamental and applied implications.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".