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Record W2773947008 · doi:10.18162/fp.2017.355

Évolution des connaissances de futurs orthopédagogues en formation initiale sur l’évaluation et

2017· article· fr· W2773947008 on OpenAlexaffvenue
Andrée Lessard, Karine-N. Tremblay

Bibliographic record

VenueFormation et profession · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Alors que les comptences valuer et intervenir auprs des lves qui prsentent des difficults en lecture sont au coeur de la pratique orthopdagogique, de nombreuses connaissances sont ncessaires leur dploiement. Cette recherche exploratoire et descriptive vise dresser un portrait de l' volution des connaissances dclares lies la pratique (valuationintervention) de futurs orthopdagogues en lien avec les difficults en lecture pendant leur formation universitaire. Les rsultats montrent qu'aprs avoir accompagn un lve en difficult dans le cadre d'une clinique universitaire en orthopdagogie (formation pratique), les tudiants nomment un plus grand nombre de connaissances en lien avec les outils, moyens et stratgies d' valuation et d'intervention sur la comprhension et l'identification des mots en lecture. Ces rsultats mettent en vidence l'apport de la formation pratique, qui amne les tudiants dclarer des connaissances avec plus de prcision. Ils seront galement discuts en fonction des contenus prsents dans le cadre de la formation initiale universitaire.

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)0.013
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.052
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0130.002

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 head0.388
GPT teacher head0.525
Teacher spread0.137 · 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 designObservational
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

Citations1
Published2017
Admission routes2
Has abstractyes

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