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Record W2115601357 · doi:10.1177/104973202129120430

The Interpersonal Contexts of Negotiating Care in Home Care Nurse-Patient Interactions

2002· article· en· W2115601357 on OpenAlexaff
Judith A. Spiers

Bibliographic record

VenueQualitative Health Research · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNegotiationInterpersonal communicationPsychologyConversation analysisConversationSocial psychologyQualitative researchTabooPower (physics)NursingPerceptionSociologyMedicineCommunication

Abstract

fetched live from OpenAlex

In this article, the author describes six interpersonal contexts within which care is negotiated between home care nurses and their patients, based on qualitative analysis of 31 videotaped visits. The interpersonal contexts were negotiation of (a) territoriality, (b) shared perceptions of the situation, (c) an amicable working relationship, (d) role synchronization, (e) knowledge, and (f) taboo topics. Analysis of moment-by-moment communication explored how social identity related to care activities is constructed, challenged, or threatened in the flow of events in the encounter. This approach does not problematize negotiation by assuming negative connotations of inequality of power; rather, it examines the therapeutic consequences of specific communication acts. It demonstrates how both nurse and patient are, paradoxically, both empowered and made vulnerable through everyday conversation.

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)0.028
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 score0.012
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0120.025
Scholarly communication0.0110.009
Open science0.0010.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.355
GPT teacher head0.542
Teacher spread0.187 · 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

Citations50
Published2002
Admission routes1
Has abstractyes

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