A psychometric evaluation of the Loss of Face Scale.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it