Attitudes and perceptions towards disability and sexuality
Bibliographic record
Abstract
PURPOSE: To describe current societal perceptions and attitudes towards sexuality and disability and how social stigma differs between individuals living with visible and invisible disabilities. METHOD: A qualitative approach was used to explore attitudes and perceptions towards sexuality and disability. Focus groups were conducted with the following groups: service providers, people with visible disabilities, people with invisible disabilities and the general public. The focus group participants viewed 'Sexability' a documentary film on sexuality and disability to stimulate discussion midway through the session. RESULTS: Findings suggest that individuals with disabilities are commonly viewed as asexual due to a predominant heteronormative idea of sex and what is considered natural. A lack of information and education on sexuality and disability was felt to be a major contributing factors towards the stigma attached to disability and sexuality. CONCLUSIONS: Stigma can lead individuals to internalise concepts of asexuality and may negatively impact confidence, desire and ability to find a partner while distorting one's overall sexual self-concept. Societal attitudes and perceptions are driven by education and knowledge, if there is no exposure to sexuality and disability, it follows suit that society would have a narrow understanding of these issues. Further research should focus on how best to educate and inform all members of society.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".