Brief Fear of Negative Evaluation scale—revised
Bibliographic record
Abstract
Rodebaugh et al. [2004: Psychol Assess 2:169-181] recently performed a confirmatory factor analysis (CFA) on the Brief Fear of Negative Evaluation scale (BFNE; Leary, 1983: Psychol Bull 9:371-375]. Their study resulted in the emergence of a two-factor solution comprising straightforwardly worded items and reverse-worded items. They concluded by recommending use of only the straightforwardly worded items in the BFNE. Our intent in this study was to evaluate this recommendation through replication and extension. Participants included 385 undergraduates from the Universities of Regina and Houston, who provided responses to a questionnaire battery including either the BFNE or a revision utilizing straightforwardly worded versions of the reverse-worded items (BFNE-II). A CFA of the BFNE, using the two-factor model proposed by Rodebaugh et al., supported their conclusion that the reverse-worded items comprise a separate, methodologically based factor. However, CFA of the BFNE-II resulted in an acceptable unitary model that conforms to the theoretical basis for the BFNE, without risking loss of sensitivity from item removal. Additional analyses suggest use of the BFNE-II rather than a shortened form.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".