Multiple Identities in Social Perception and Interaction: Challenges and Opportunities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Categorization plays a fundamental role in organizing daily interactions with the social world. However, there is increasing recognition that social categorization is often complex, both because category membership can be ambiguous (e.g., multiracial or transgender identities) and because different categorical identities (e.g., race and gender) may interact to determine the meaning of category membership. These complex identities simultaneously impact social perceivers' impressions and social targets' own experiences of identity, thereby shaping perceptions, experiences, and interactions in fundamental ways. This review examines recent research on the perception and experience of the complex, multifaceted identities that both complicate and enrich our lives. Although research has historically tended to focus more on difficulties and challenges associated with multiple identities, increasing attention is being paid to opportunities that emerge from the possession of identities that include multiple distinct or overlapping groups. We consider how these opportunities might benefit both perceivers and targets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it