Building a Definition of Irritability From Academic Definitions and Lay Descriptions
Why this work is in the frame
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Bibliographic record
Abstract
The current work builds a definition of irritability from both academic definitions and lay perspectives. In Study 1, a quantitative content analysis of academic definitions resulted in eight main content categories (i.e., behaviour, emotion or affect, cognition, physiological, qualifiers, irritant, stability or endurance, and other). In Study 2, a community sample of 39 adults participated in qualitative interviews. A deductive thematic analysis resulted in two main themes. The first main theme dealt with how participants positioned irritability in relation to other negative states. The second dealt with how participants constructed irritability as both a loss of control and as an experience that should be controlled. The discussion integrates the findings of both studies and provides a concise, but comprehensive definition.
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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