Internalizing the closet: Concealment heightens the cognitive distinction between public and private selves.
Bibliographic record
Abstract
The present studies are the first in which social psychological methods were used to test the popular claim that the experience of concealing a stigmatized social identity leads to a "divided self." For people with concealable stigmas, concealment in public settings makes the public-private dimension of self-expression particularly salient, leading them to organize self-relevant information along this dimension. The result is a strengthened cognitive distinction between public and private aspects of the self, what we have termed public-private schematization. We developed and tested a measure of the cognitive accessibility of the distinction between public and private self-schemas by measuring how quickly participants sorted trait attributes into self-in-public (e.g., self-at-work) and self-in-private (e.g., self-at-home). People with more accessible distinct public and private self-schemas should be faster at categorizing trait attributes into public- and private-self aspects than those with more integrated public and private self-schemas. Relative to people without such identities, people with concealable stigmas (Study 1a, sexual orientation; Study 1b, religiosity at a secular college), show greater public-private schematization. This schematization is linked to concealment (Study 2) and to the experimental activation of concealable versus conspicuous stigmatized identities (Study 3). Implications of distinct public and private self-schemas for psychological well-being are explored in Studies 4 and 5. Two different measures of distress-perceived social stress (Study 4) and depressive symptoms (Study 5)-provided evidence showing that the accessibility of the distinction between public and private self-schemas accounted for the association of concealment on heightened distress. Implications for research on concealment and self-structure 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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".