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Who's Users? Participation and Empowerment in Socio-Technical Approaches to Health IT Developments

2011· article· en· W130127737 on OpenAlex
André Kushniruk

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStudies in health technology and informatics · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEmpowermentPatient EmpowermentSociotechnical systemComputer scienceInternet privacyKnowledge managementPolitical science

Abstract

fetched live from OpenAlex

Health informatics researchers advocating socio-technical approaches to the design, implementation and evaluation of health information technology (HIT) consistently promote the important role of users. Aside from conventional ethical and legal considerations around their involvement, there are a number of philosophical and methodological issues that have received less attention because of the tendency for researchers to assume the term 'user' is well defined and understood. It is however, evident that there are significant differences amongst users, and differences in how researchers engage, involve and interact with them during health IT developments. Failure to acknowledge these differences and their impact on Health IT developments makes comparisons across different studies problematic and raises fundamental questions about participation and empowerment of end-users in our developments. This paper re-examines the term user in the context of socio-technical approaches to HIT and presents a preliminary approach to differentiating between types of users and our changing expectations of their roles in enhancing different HIT projects across design, implementation and evaluation.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.263
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.319
GPT teacher head0.448
Teacher spread0.129 · 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