In perfect harmony: Synchronizing the self to activated social categories.
Bibliographic record
Abstract
The self-concept is one of the main organizing constructs in the behavioral sciences because it influences how people interpret their environment, the choices they make, whether and how they initiate action, and the pursuit of specific goals. Because belonging to social groups and feeling interconnected is critical to human survival, the authors propose that people spontaneously change their working self-concept so that they are more similar to salient social categories. Specifically, 4 studies investigated whether activating a variety of social categories (i.e., jocks, hippies, the overweight, Blacks, and Asians) increased associations between the self and the target category. Whereas Studies 1 and 2 focused on associations between stereotypic traits and the self, Studies 3 and 4 examined self-perceptions and self-categorizations, respectively. The results provide consistent evidence that following social category priming, people synchronized the self to the activated category. Furthermore, the findings indicate that factors that influence category activation, such as social goals, and factors that induce a focus on the interconnectedness of the self, such as an interdependent vs. independent self-construal, can impact this process. The implications of changes to the working self-concept for intergroup relations are discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".