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Record W4387578172 · doi:10.12927/hcpol.2023.27175

Patient Partners Respond to High-Level Findings on the Connectedness of Health and Social Services across Canada

2023· article· en· W4387578172 on OpenAlexaffvenueabout
Jeannie Haggerty, Catherine M. Scott

Bibliographic record

VenueHealthcare policy · 2023
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of CalgaryMcGill University Health Centre
Fundersnot available
KeywordsSocial connectednessNorm (philosophy)Public relationsConnection (principal bundle)Health servicesPsychologySocial psychologyPolitical scienceMedicineEnvironmental healthEngineeringLaw

Abstract

fetched live from OpenAlex

This short article captures input from patient partners on the dimensions of the research program that most resonated with them.They are passionate about wanting to see a better connection between health and social services, and they are also willing to be involved as advisors for policy directions in the same way as their involvement has become the norm in any patient-oriented research. RésuméCe court article présente les commentaires de patients partenaires sur les aspects du programme de recherche qui les ont le plus interpellés.Ils sont avides de voir un meilleur lien entre la santé et les services sociaux, et ils sont également prêts à participer en tant que conseillers pour les orientations stratégiques comme ils le font déjà pour toute recherche axée sur le patient, où leur participation est désormais la norme.

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)0.010
metaresearch head score (Gemma)0.033
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: none
Teacher disagreement score0.299
Threshold uncertainty score0.601

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0230.005
Scholarly communication0.0070.003
Open science0.0010.010
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0090.000

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 head0.325
GPT teacher head0.500
Teacher spread0.175 · 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

Citations1
Published2023
Admission routes3
Has abstractyes

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