The relevance appraisal matrix: Evaluating others’ relevance.
Bibliographic record
Abstract
People seek to detect who facilitates and who impedes their goal pursuit. The resulting relevance appraisals of opportunity and threat, respectively, can strongly shape subsequent social judgment and behavior. However, important questions about the nature of relevance appraisals remain unanswered: Are relevance appraisals unidimensional or multidimensional? Are people evaluated as generally posing opportunities and/or threats, or as dynamically relevant depending on perceiver goals? We test two hypotheses. First, we propose that opportunity and threat are appraised independently, rather than as endpoints of a single dimension. If so, then others can be evaluated as (a) facilitating a goal, (b) impeding a goal, (c) both facilitating and impeding a goal, or (d) neither facilitating nor impeding a goal. Second, we hypothesize that relevance appraisals shift dynamically with perceiver goals. For example, a single person may be appraised as facilitating one's mate-seeking goal, but as neither facilitating nor impeding one's self-protection goal. In two studies, participants rated the extent to which a variety of targets (e.g., a doctor, a 5-year-old child) pose threats and opportunities to different goals. Confirmatory factor analyses support both hypotheses. We also explore relationships between the Relevance Appraisal Matrix and the stereotype content (Fiske et al., 2002) and ABC (Koch et al., 2016) models of stereotypes, finding evidence that relevance appraisals are distinct from stereotypes of group attributes. In sum, we provide a framework for understanding the structure of relevance appraisals: A central and consequential, yet dynamic and relatively understudied, aspect of social cognition. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".