The Need for Affect: Individual Differences in the Motivation to Approach or Avoid Emotions
Bibliographic record
Abstract
The present research developed and tested a new individual-difference measure of the need for affect, which is the motivation to approach or avoid emotion-inducing situations. The first phase of the research developed the need for affect scale. The second phase revealed that the need for affect is related to a number of individual differences in cognitive processes (e.g., need for cognition, need for closure), emotional processes (e.g., affect intensity, repression-sensitization), behavioral inhibition and activation (e.g., sensation seeking), and aspects of personality (Big Five dimensions) in the expected directions, while not being redundant with them. The third phase of the research indicated that, compared to people low in the need for affect, people high in the need for affect are more likely to (a) possess extreme attitudes across a variety of issues, (b) choose to view emotional movies, and (c) become involved in an emotion-inducing event (the death of Princess Diana). Overall, the results indicate that the need for affect is an important construct in understanding emotion-related processes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".