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Record W2966287423 · doi:10.1177/0952695119850716

The ‘disabilitization’ of medicine: The emergence of Quality of Life as a space to interrogate the concept of the medical model

2019· article· en· W2966287423 on OpenAlexaff
Arseli Dokumacı

Bibliographic record

VenueHistory of the Human Sciences · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsConcordia University
FundersH2020 European Research Council
KeywordsQuality of life (healthcare)Set (abstract data type)Space (punctuation)PsychologyEveryday lifeActivities of daily livingGazeDistressEpistemologyCognitive psychologyMedicinePsychotherapistPsychoanalysisComputer sciencePsychiatryPhilosophy

Abstract

fetched live from OpenAlex

This article presents an archaeological inquiry into the early histories of Quality of Life (QoL) measures, and takes this as an occasion to rethink the concept of the ‘medical model of disability’. Focusing on three instruments that set the ground for the emergence of QoL measures, namely, the Karnofsky Performance Scale (KPS, 1948), and the classification of functional capacity as a diagnostic criterion for heart diseases (Bainton, 1928) and as a supplementary aid to therapeutic criteria in rheumatoid arthritis ( Steinbrocker, Traeger, and Batterman, 1949 ) – I discuss how medicine, throughout the emergence of QoL, began to expand its gaze beyond the confines of the body to what that body does in daily life. Building upon Armstrong et al.’s notion of ‘distal symptoms’ (2007) and Wahlberg’s idea of ‘knowledge of living’ (2018), I propose the notion of disabilitization to encapsulate this expansion of the clinical gaze, through which medicine has come to articulate diseases and their treatments in new ways, and in so doing, has inadvertently created disability as a new kind of knowledge category in itself – a category that is defined not through its reduction to mere pathology, but through its dispersal into everyday life. I present this concept not as a periodization, but as a provocative discontinuity with the totalizing history assumed within the medical model of disability, and in so doing, ask what, in fact, holds ‘the medical model’ together, and whether there might be other ways of understanding medicine’s complex relationship to disability than what the concept of the medical model allows us to envisage.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.029
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.095
GPT teacher head0.401
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2019
Admission routes1
Has abstractyes

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