Bibliographic record
Abstract
The Commitment Theory of Emotions is issued from a careful scrutiny of emotional behavior in humans and animals, as reported in the literature on Evolutionary Biology, Neurosciences and the Psychology of emotions. Emotions are viewed as a special layer of processes, wired upon needs and instincts, and dealing mainly with nurturance, social bonding and cooperative behavior, especially between kin and relatives. As every other motivational system, they operate so as to manage resources critical for survival and reproduction. The peculiar resources emotions do manage are commitments, understood as the predispositions of a given individual to help others and collaborate with them in a reciprocal manner. This view clarifies considerably the interactions emotions entertain with a variety of modules involved in their operation, from the detection of antecedents in perceptual or memory systems, to the elicitation of the appropriate emotion, to the execution of the corresponding script, to the expression of emotions as the typical outcome of emotional episodes. The flow of processing is continuously modulated by affective states of the organisms and by other motivational systems. The chapter expounds the operation of each module as well as their interactions with each other. It concludes that successful implementation of emotions in artificial systems will have to rest upon the specifications of complex and realistic models of the kind presented.
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How this classification was reachedexpand
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 | 0.002 |
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; both teacher heads agree on what is shown here.
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".