The art of coping with a craniofacial difference: Helping others through “Positive Exposure”
Bibliographic record
Abstract
Finding ways to cope with social stigmatization is an important aspect of achieving adaptation for people living with visible genetic differences. This study describes the way individuals with craniofacial differences use an innovative photography and video experience with Positive Exposure (PE), a non-profit organization based in New York City, as a way to cope with their conditions. Thirty-five individuals between 12 and 61 years of age participated in this study. We administered surveys comprised of open-ended qualitative questions and quantitative measures designed to assess self-esteem, perceived stigma, and hopefulness. Data for this analysis was generated from the written questionnaires and interview transcripts. Most participants reported high levels of self-esteem and hopefulness, suggesting that they were relatively well adapted to their condition. Almost all participants described experiences of stigmatization throughout their lives. However, participants demonstrated their ability to implement a variety of coping strategies to manage stigma. "Helping others" emerged as a prominent strategy among participants, aiding in the often lifelong process of adapting to their genetic difference. PE was described as an avenue through which participants could reach out to individuals and society at large, helping them adapt further to their condition. "Helping others" may also benefit individuals with craniofacial differences who do not consider themselves to be well adapted to their condition. Health care providers can collaborate with PE, advocacy groups and other community or support groups to identify additional ways individuals with craniofacial differences can help themselves by reaching out to others.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".