Bibliographic record
Abstract
This chapter describes and explains emotions in terms of their relationship with goals using a control theory approach. A comprehensive and widely cited overview of goals in psychology defined a goal as ‘internal representations of desired states, where states are broadly construed as outcomes, events or processes’ (Austin & Vancouver, 1996). Austin and Vancouver (1996) go on to give examples of these desired states, which include biological set points (e.g. body temperature) and abstractions of complex outcomes (e.g. career success, which could include achieving goals in sport), encompass wide-ranging durations from the present moment to the lifespan, and span the domains of the neurological, psychological, and social. Please note that goals in the psychological literature are much wider than the way that the term ‘goal’ is used in common parlance. A goal can include abstract, socially relevant set points such as being honest, worthwhile, or creative, as well as simple, concrete set points such as gripping a racquet tightly or keeping balance while in motion. Importantly, these authors found it necessary to use an organizing theoretical framework with specific operational definitions of its components for their review, and they used a form of control theory developed by Powers, often known as perceptual control theory (Powers, 1973, 2005). This chapter will begin with a rationale for why emotions can be understood in relation to goals. The wider literature on goals and emotions will be reviewed in order to describe the current state of knowledge in this area, and then the control theory model will be used to elaborate and describe a mechanistic, functional account of the role of emotions. This account will be divided into the components of control theory, explaining their relevance to emotion, and it will conclude with the implications of a goal-oriented approach to emotion informed by control theory. The chapter begins with an open-minded approach to the role of emotion within what is often regarded as a relatively mechanistic and ‘cold’ account – ‘goals’ and ‘control theory’. Yet the chapter converges on a conclusion that emotion exists in almost every feature of goal functioning, both unconscious and conscious, interpersonal and intrapersonal, and that emotions are a fundamental marker of the dynamic features of goals, such as conflict, higher-level perspective-taking, and change.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".