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Record W69509063 · doi:10.1055/s-0038-1634225

Getting the Big Picture

2003· article· en· W69509063 on OpenAlexafffund
Ellen Balka

Bibliographic record

VenueMethods of Information in Medicine · 2003
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaHealth Canada
KeywordsMedicine

Abstract

fetched live from OpenAlex

OBJECTIVES: While recognized that global actors influence health information system design, studies of health informatics have largely focused on micro politics of technology design and implementation. Here a problematic patient care information system (PCIS) is discussed in relation to federal and provincial policies and corporate strategies to demonstrate that our understanding of health informatics can be enhanced by linking micro studies of health informatics to larger macro contexts. METHODS: Interviews and document study. RESULTS: Although the extent to which federal initiatives influenced (or failed to influence) provincial and hospital initiatives remains debateable, events initiated at one level (the hospital's decision to implement software, initiated at the organizational level) are influenced (perhaps indirectly) by developments in other contexts (federal/macro changes gave an initiative more weight; provincial initiatives such as the Labour Accord altered the industrial relations environment in which system development occurred). CONCLUSIONS: Micro-studies of work practice, invaluable in addressing interactions between technologies, users and work practices, often fail to account for the historic reach of global actors, although it is often these historic circumstances that contribute to present-day interactions between user, information system and organization, and that find expression - often indirectly - in daily work practices.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.102
GPT teacher head0.534
Teacher spread0.432 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations59
Published2003
Admission routes2
Has abstractyes

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