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Record W2046405686 · doi:10.1300/j045v19n03_01

The Story Behind the Story of Collaborative Networks–Relationships Do Matter!

2004· article· en· W2046405686 on OpenAlexaffabout
Judith M. Dunlop, Michael J. Holosko

Bibliographic record

VenueJournal of Health & Social Policy · 2004
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPublic relationsInterpersonal communicationSubject matterInterpersonal relationshipQualitative researchConceptual frameworkResource (disambiguation)Subject (documents)Knowledge managementSociologyBusinessPsychologyPolitical scienceSocial psychologyPedagogySocial scienceLibrary science

Abstract

fetched live from OpenAlex

This study reports data about the real story behind the current trend of mandated interorganizational collaboration of health and human service agencies. By means of qualitative design (N-22), public health managers were interviewed about the extent and nature of their collaborative efforts in the Healthy Babies, Healthy Children (HBHC) Program in Ontario, Canada. Using a conceptual framework of resource exchange theory, this study found that relational processes specifically: (a) previous relationships with other agencies and (b) interpersonal relations namely: informality, local community, open communication and resolving conflicts were the reasons for successful collaborations. Implications are directed toward: health and social planners, administrators, board members, funding bodies and policy-makers. The study offers new knowledge about a subject which has received minimal attention in the literature.

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)0.009
metaresearch head score (Gemma)0.025
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 score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0250.039
Scholarly communication0.0140.033
Open science0.0020.009
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0040.001

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 head0.083
GPT teacher head0.462
Teacher spread0.379 · 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

Citations27
Published2004
Admission routes2
Has abstractyes

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