A psychometric evaluation of the Loss of Face Scale.
Bibliographic record
Abstract
Face and loss of face (LOF) are important social and clinical constructs in many cultures. The present study evaluated the psychometric properties of the LOF Scale in 4 samples of European Americans and Asian Americans with a total of 2,057 participants. We found LOF Scale scores to have high internal reliability across all samples. Confirmatory factor analyses comparing 1- and 2-factor models supported a 1-factor structure for both European and Asian Americans, albeit 4 items (Items 3, 13, 14, and 20) were found to be noninvariant across the 2 groups. Two error covariances between Items 2 and 3, and between Items 11 and 20 were both substantial and invariant across groups. Tests of latent mean differences revealed a mean LOF score that was significantly higher for Asian Americans than for European Americans. Finally, the LOF scores correlated with affective distress and self-construal equally for Asian Americans and European Americans, correlated with some factors in collective self-esteem for both groups, and correlated with acculturation for Asian Americans. These results supported the LOF Scale as a psychometrically sound tool for assessing the unidimensional concept of the LOF across cultures. (PsycINFO Database Record
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".