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Record W317650484

La Classification québécoise dite Processus de production du handicap peut-elle contribuer à la production de connaissances et aider à la prise de décisions ?

2010· article· fr· W317650484 on OpenAlexaboutno aff
Joèlle Canton

Bibliographic record

Venueinteractions · 2010
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)PsychologyComplement (music)Set (abstract data type)HumanitiesLinguisticsComputer sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

A study run by the “Quebecois Committee on the International Classification of Impairment Disabilities and handicaps” at the same time as the revision process of the I.C.I.D.H. led to the production of a “classification” distinct from that of the WHO. The third version of this “classification”, known as “Processus de production du handicap” released in 1998 – considered by its developers as a final, accomplished and validated version – seems to place itself more as a competitor than as a complement to the WHO classification. Although called “Classification”, this text is in fact made up of five distinct documents entitled “nomenclature” none of which have the formal properties of a classification. The expression “Processus de production du handicap” does not refer to a delimited set of objects or types susceptible to be classified, but is the proper noun of a “model” which claims to be “an explicative model of the diseases, traumatisms and other attacks of the integrity and development of the individual”. The analysis of the different nomenclatures shows that they have not been designed to serve the general purpose of “explanation” of the “Processus de production du handicap” in other words the “process of production of social exclusion”, and they can’t claim to contribute in a notable way to this explanation. On the contrary, the main purpose according to which these documents have been conceived seems to be to provide “experts” the means to draw up “individual profiles” based on judgments passed on individuals, on the nature and extent of their “needs”, their belonging to a “target group”, and their right to compensation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.188
Threshold uncertainty score0.378

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0090.020
Scholarly communication0.0160.008
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0100.003

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 head0.063
GPT teacher head0.444
Teacher spread0.381 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2010
Admission routes1
Has abstractyes

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