Person-first and identity-first disability language: Informing client centred care
Bibliographic record
Abstract
BACKGROUND: Addressing individuals with a disability can entail the use of person-first (person with a disability) or identity-first language (disabled person). However, there has been debate about use of these terms, yet there is a lack of evidence to inform preference across people with a broad range of health conditions, demographics, or health related factors. METHODS: A 42-item survey measuring demographic and health condition factors, implicit and explicit preference for person-first and identity-first language use was open for completion by individuals with a self-reported health condition between July 7, 2021 and November 30, 2021. Recruitment was undertaken via posts on relevant social media sites and through community support and advocacy organisations. RESULTS: Data analysis included responses from 875 valid surveys. Mean age of participants was 39.7 (SD: 13.7) years. There were 89 (10.2%) male, 637 female (72.8%) and 149 (17.0%) non-binary/other participants. When referring to themselves, participants most often reported use of identity first language (n = 335, 42.2%), followed by person-first language (n = 272, 34.1%), then both interchangeably (118, 23.7%). When referring to others, participants most often used person first language (n = 312, 39.4%), followed by both interchangeably (269, 34.0%), then identity-first language (n = 211, 26.6%). Disability language preference varied across health conditions, with participants with neurodevelopmental conditions most likely to use identity-first language and participants with digestive conditions most often preferencing person-first language. Participants who were younger and of non-binary gender preferred use of identity-first language. Appropriate use of identity-first language was rated significantly higher for people with a disability/health condition and family/friends than for third-party representatives, including healthcare professionals, educators, media and the general public. CONCLUSION: Findings highlight the need to understand health condition and disability language preference in a more nuanced way to promote respectful language use when addressing people in the context of their disability/health condition.
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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 | 0.066 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".