What Motives Do People Most Want to Know About When Meeting Another Person? An Investigation Into Prioritization of Information About Seven Fundamental Motives
Bibliographic record
Abstract
What information about a person’s personality do people want to know? Prior research has focused on behavioral traits, but personality is also characterized in terms of motives. Four studies ( N = 1,502) assessed participants’ interest in information about seven fundamental social motives (self-protection, disease avoidance, affiliation, status, mate seeking, mate retention, kin care) across 12 experimental conditions that presented details about the person or situation. In the absence of details about specific situations, participants most highly prioritized learning about kin care and mate retention motives. There was some variability across conditions, but the kin care motive was consistently highly prioritized. Additional results from Studies 1 to 4 and Study 5 ( N = 174) showed the most highly prioritized motives were perceived to be stable across time and to be especially diagnostic of a person’s trustworthiness, warmth, competence, and dependability. Findings are discussed in relation to research on fundamental social motives and pragmatic perspectives on person perception.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".