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Record W4391889994 · doi:10.1177/11786329241232299

Can Implementing New Services Organization Models to Better Meet the Needs of Young People Bring About Practice Changes? Analysis of an Experiment in Québec

2024· article· en· W4391889994 on OpenAlexafffundabout
Nassera Touati, Isabelle Ruelland, Lourdes Rodríguez del Barrio, Marie J. Bouchard, Katherine Beaulieu, Isabelle Courcy

Bibliographic record

VenueHealth Services Insights · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalÉcole Nationale d'Administration Publique
FundersFonds de Recherche du Québec - Santé
KeywordsContext (archaeology)GRASPIntervention (counseling)Public relationsWork (physics)Activity theoryKnowledge managementBest practiceProcess managementSociologyPsychologyBusinessComputer sciencePolitical scienceMedicineNursingEngineeringPedagogy

Abstract

fetched live from OpenAlex

The research question addressed in this article is: Can implementing new services organization models to better meet the needs of young people bring about practice changes? More precisely, we examine the effects of a new model called Aire Ouverte (AO) which is implemented gradually across Quebec since 2019. This new model involves public sector and community organizations. To grasp practices' change, we use cultural historical activity theory (CHAT) and employ a qualitative approach. Beyond a precise description of work activities, we gained an inside view of how the actors involved represented their practice and context. Our results show that practice changes seen by actors are in line with the object of the intervention, that is, responding rapidly to the expressed needs of young people. The development of new tools, flexible functioning, strengthening of interprofessional and intersectoral collaboration, involvement of young people in decision-making, all should contribute to improving response to their needs. This being said, a critical look at practice changes reveals a challenge in aligning the design and objective of AO with the needs of some young people. We noted also a poor alignment of effective collaborative practices between levels of care and the practices sought from intersectoral collaboration.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.102
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.006
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.352
Teacher spread0.327 · 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.

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
Published2024
Admission routes3
Has abstractyes

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