Bibliographic record
Abstract
The field of disability history began to develop in the 1990s, as part of politically engaged scholarship concerning disabled people. 1 Seeking to address harmful stereotypes and to amplify the voices of disabled people, historical research into disability can be considered a tool of disability activism.Scholarship in this field, drawing on the "social model of disability", has focused on the social construction of disability and impairment across different historical contexts, cultures, and time periods, as well as groups of people. 2 As such, disability, alongside other forms of marginality like Deafness and neurodivergence can be understood as analytical perspectives on which historians can draw, in a similar fashion to race, gender, sexuality, or class.3 In turn, this provides for a myriad interdisciplinary and intersectional research opportunities with other fields and marginalized groups to promote new insights 1 Daniel Blackie and Alexia Moncrieff, "State of the Field: Disability History", History 107, no.377 (2022): 2-3. 2 The social model of disability refers to the principle that disability is a socially created identity, enforced onto certain groups of people due to physical, psychological, or behavioural impairments.This model moves the locus of disability from individual deficit to structural and societal powers; Tom Shakespeare, "The Social Model of Disability", in The Disability Studies Reader, ed.Lennard J. Davis (New York: Routledge, 2010), 197; Michael Rembis, "Challenging the Impairment/Disability Divide: Disability History and the Social Model of Disability", in The Routledge Handbook of Disability Studies, ed.Nick Watson and Simo Vehmas (New York: Routledge, 2019), 379. 3 This article generally uses language referring to disability and marginality present in the publications highlighted.The term "marginality" is used as an umbrella for different groups of disabled and neurodivergent people, alongside others ostracized socially and economically.Language around Deaf people and Deafness generally uses the capital "D" to refer to the specific identity of Deaf communities and identities.However, in some circumstances, deaf or D/deaf is used to refer to hearing-impaired groups broadly.In my research I recognize the identity and communal differences between Deaf and deaf groups; see Jemina Napier, "The D/Deaf-H/Hearing Debate", Sign Language Studies 2, no. 2 (2002): 141-2; Blackie and Moncrieff, "State of the Field", 4-5.For ethical and research implications for the D/deaf perspective, see also
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".