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
A person's judgeability, or the extent to which a person is easy to understand, plays an important role in how accurately a target will be perceived by others. Research on this topic, however, has not been systematic or well-integrated. The current review begins to remedy this by integrating the available research on judgeability from the fields of personality perception, nonverbal communication, and social cognition. Specifically, this review summarizes the characteristics that are likely to promote judgeability and explores its potential consequences. A diverse range of characteristics are identified as predictors of judgeability, all relating to three broader categories: psychological adjustment, social status, and socialization. Furthermore, being judgeable has a variety of potential, largely positive, consequences for the target, leaving good targets poised for greater personal and interpersonal well-being. Nevertheless, many questions on this topic remain and it is crucial for this relatively understudied topic to receive more systematic empirical attention.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it