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Record W3083378607 · doi:10.46278/j.ncacn.20170913

Phénomènes de dépendance à l’environnement et conformisme social : intérêts d’une approche interactionniste en neuropsychologie clinique

2017· article· fr· W3083378607 on OpenAlexvenueno aff
Jeremy Besnar, Morgane Pallone, Ghislaine Aubin, Laëtitia Ferracci, Caroline Racineux, Philippe Allain

Bibliographic record

VenueNeuropsychologie clinique et appliquée · 2017
Typearticle
Languagefr
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesValuation (finance)PhilosophySociologyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Nous décrivons le cas d’un patient victime d’un traumatisme crânien, responsable de lésions frontales et temporales bilatérales. Ce patient présentait des troubles exécutifs ainsi que des perturbations comportementales, principalement sous forme d’une dépendance à l’environnement. L’objectif de la présente étude était double. D’une part, nous souhaitions évaluer la pertinence d’une interprétation socio-cognitive de la dépendance à l’environnement, au moyen d’un dispositif évaluant le conformisme social, impliquant des situations d’interaction réelle et virtuelle. D’autre part, nous souhaitions étudier l’influence du type de situation sur le conformisme social, de rares études démontrant des différences de performances selon le type d’évaluation (réel ou virtuel). Les résultats démontrent des dissociations de performance en fonction du mode d’évaluation. Le conformisme n’est constaté que lors de l’évaluation en environnement réel. L’intérêt de l’approche interactionniste pour la mise en évidence de troubles socio-comportementaux et le bénéfice des environnements virtuels pour l’évaluation neuropsychologique sont discutés.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.109
GPT teacher head0.483
Teacher spread0.375 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

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