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Record W2960339895 · doi:10.1108/jsm-02-2019-0081

Non-medical health centers – directions for service researchers

2019· article· en· W2960339895 on OpenAlexaff
Troy D. Glover, Diana C. Parry

Bibliographic record

VenueJournal of Services Marketing · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOriginalityPublic relationsHealth careSalience (neuroscience)Transformative learningCITESSociologyPsychologyQualitative researchPolitical science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to provide directions for research on non-medical health service and servicescapes by building off Rosenbaum’s study of social support for men at a resource center for testicular cancer. Design/methodology/approach This paper cites literature and introduces directions for future research. Findings This paper contains insights on non-medical health services and servicescapes, including the salience of social connection for coping, the need to connect with others who are experiencing the same health issue, the relevance of place and face-to-face contact, the role of leisure in drawing people together and the need to look at these environments critically. Originality/value This viewpoint provides insights to anyone interested in transformative service research, particularly those who apply this approach to study health-care services.

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)0.085
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.085
Threshold uncertainty score0.449

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0850.067
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.007
Science and technology studies0.0160.028
Scholarly communication0.0250.044
Open science0.0070.021
Research integrity0.0170.023
Insufficient payload (model declined to judge)0.0250.004

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 head0.155
GPT teacher head0.467
Teacher spread0.312 · 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 designTheoretical or conceptual
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

Citations3
Published2019
Admission routes1
Has abstractyes

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