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Record W2168686029 · doi:10.1057/palgrave.jmm.5050070

From service factory to service theatre: Solving the positioning dilemma in the medical practice

2007· article· en· W2168686029 on OpenAlexaff
Jean‐Paul Berthon, Mélani Prinsloo, Leyland Pitt

Bibliographic record

VenueJournal of Medical Marketing Device Diagnostic and Pharmaceutical Marketing · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDilemmaService (business)Factory (object-oriented programming)NothingFront officeBusinessDramaturgyMarketingOperations managementPublic relationsComputer scienceEngineeringAestheticsPolitical scienceArtEpistemology

Abstract

fetched live from OpenAlex

Doctor's surgeries are typically inefficient: They are generally stuck in the middle of the market, neither providing an individually tailored personal experience, nor one that is fast, efficient and cost effective. Introducing ideas from service simultaneity, and dramaturgy (the theory and practice of dramatic composition), this paper provides a simple but powerful model for the conceptualisation and redesign of the doctor's surgery. We argue that doctor's surgeries that are successful will be those that focus either on standardisation of activities in a back office environment (Service Factory), or high customisation of activities in a front office environment (Service Theatre). Those that attempt to do everything will succeed in doing nothing well.

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)0.033
metaresearch head score (Gemma)0.049
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0270.105
Scholarly communication0.0240.030
Open science0.0030.016
Research integrity0.0240.023
Insufficient payload (model declined to judge)0.0120.003

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 head0.023
GPT teacher head0.312
Teacher spread0.289 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

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