A Simplified Framework for Working with Emotions
Bibliographic record
Abstract
Emotion is a key element of interpersonal relations, and emotion-related difficulties are one of the leading causes of suffering and failure to adapt to the demands of life. Viewing “emotions as a symptom” via the medical model—or even emotions as “goals” in themselves— seems to continue to contribute harms to individuals via the consequences and side effects of psychophrarmaceutical and substance use, along with general losses of human potential. This paper is an investigation of the relationship between emotions (here broadly defined as a motivating factor driving behaviour and memory formation), perception, goals, and the difficulty of achieving goals. A model of emotional self-regulation termed the personal world model is constructed with the aid of a literature review, proposing emotion as the central process underlying all human self-regulatory functioning. The model is tested and refined using data from the Statistics Canada 2002 Canadian Community Health Survey. Recommendations are made as to possible applications and use of this model in future studies and during psychotherapy training and practice.
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.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".