A Test to Measure the Awareness and Expression of Anger
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
The purpose of this project was to develop a reliable, objective and practical tool with which the awareness and expression of anger could be investigated. This paper gives a description of the Awareness and Expression of Anger Indicator (AEAI). The AEAI is a short and easy to use test. It provides a new objective assessment instrument of value in cases where deficits in affective processes, particularly anger, are suspected. 30 medical patients were tested with the AEAI. The investigators report a high inter-rater reliability in scoring the test. Four distinct response patterns emerged. Also, when confronted with the same anger-provoking stimulus, subjects responded significantly differently with respect to whether or not they felt angry, depending on the type of question. Traditional inducing questions, e.g.: Would you feel angry?, produced significantly more affirmative responses (reports of feeling angry) than non-inducing questions, e.g.: How would you feel? The contribution of the AEAI to chronic pain work is discussed.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it