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Record W1965722666 · doi:10.1300/j027v23n03_01

Interdisciplinary Team Processes Within an In-Home Service Delivery Organization

2004· article· en· W1965722666 on OpenAlexaff
Thomas W. Gantert, Carol L. McWilliam

Bibliographic record

VenueHome Health Care Services Quarterly · 2004
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsWestern University
Fundersnot available
KeywordsTeamworkGrounded theoryContext (archaeology)Health careExploratory researchNursingPsychologyKnowledge managementQualitative researchSociologyMedicineComputer scienceManagement

Abstract

fetched live from OpenAlex

Interdisciplinary teamwork is particularly difficult to achieve in the community context where geographical separateness and solo practices impede face to face contact and collaborative practice. Understanding the processes that occur within interdisciplinary teams is imperative, since client outcomes are influenced by interdisciplinary teamwork. The purpose of this exploratory study was to describe the processes that occur within interdisciplinary teams that deliver in-home care. Applying grounded theory methodology, the researcher conducted unstructured in-depth interviews with a purposeful sample of healthcare providers and used constant comparative analysis to elicit the findings. Findings revealed three key team processes: networking, navigating, and aligning. The descriptions afford several insights that are applicable to in-home healthcare agencies attempting to achieve effective interdisciplinary team functioning.

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)0.006
metaresearch head score (Gemma)0.012
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 score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.375
Teacher spread0.363 · 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

Citations17
Published2004
Admission routes1
Has abstractyes

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