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Record W7029654777

La collaboration interprofessionnelle : cas d’un service de pédiatrie d’un hôpital universitaire au Liban

2011· dissertation· fr· W7029654777 on OpenAlexfundno aff

Bibliographic record

VenueBase Institutionnelle de Recherche de l'université Paris-Dauphine (BIRD) (University Paris-Dauphine) · 2011
Typedissertation
Languagefr
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
FundersHealth CanadaWorld Bank Group
KeywordsContext (archaeology)Service (business)FrugalityLimiting
DOInot available

Abstract

fetched live from OpenAlex

Interprofessional collaboration (IPC) is an innovating concept which emerges in organization and management theory and which is mostly applied to the health sector. As a response to the evidence found in the literature as to the lack of precise definitions of IPC and to the existence of many underlying concepts which renders its applicability difficult, we propose a generic definition and three contextualized definitions of IPC based on the empirical study conducted in three wards of a pediatric unit of a teaching hospital in Lebanon. The case study approach used in this research allows us to compare between the three units, to propose models of IPC which take into consideration the specific environment of each unit and to develop a generic model of IPC. The unique interview grid on which is based this work limits bias from the researcher and subjectivity of the actors. This tool allows us to highlight the perception of actors of the IPC, the potential situations of IPC, forms of IPC, prerequisites of IPC, facilitating and restrictive factors of IPC and the outcomes.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0090.004
Scholarly communication0.0050.002
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.061
GPT teacher head0.345
Teacher spread0.284 · 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 designQualitative
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
Published2011
Admission routes1
Has abstractyes

Explore more

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