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Record W7052014397

Plug-in healthcare: Development, ruination, and repair in health information exchange

2023· dissertation· en· W7052014397 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsSociotechnical systemPremiseWork (physics)ReflexivityInformation exchangeHealth careGovernment (linguistics)Information technology
DOInot available

Abstract

fetched live from OpenAlex

This dissertation explores the work done by people and things in emerging infrastructures for health information exchange. It shows how this work relates to processes of development, production, and growth, as well as to abandonment, ruination, and loss. It argues for a revaluation of repair work: a form of articulation work that attends to gaps and disruptions in the margins of technological development. Often ignored by engineers, policy makers, and researchers, repair sensitizes us to different ways of caring for people and things that do not fit, fall in between categories, and resist social norms and conventions. It reminds us that infrastructures emerge in messy and unevenly distributed sociotechnical configurations, and that technological solutions cannot be simply ‘plugged in’ at will, but require all kinds of work. With that, repair emphasizes the need for more democratic, critical, and reflexive engagements with (and interventions in) health information exchange. Empirically, this study aims to understand how ‘integration’ in health information exchange is done in practice, and to develop concepts and insights that may help us to rethink technological development accordingly. It starts from the premise that the introduction of IT in healthcare is all too often regarded as a neutral process, and as a rational implementation challenge. These widespread views among professionals, managers, and policy makers need to be addressed, as they have very real – and mostly undesirable – consequences. Spanning a period of more than ten years, this study traces the birth and demise of an online regional health portal in the Netherlands (2009-2019). Combining ethnographic research with an experimental form of archive work, it describes sociotechnical networks that expanded, collapsed, and reconfigured around a variety of problems – from access to information and data ownership to business cases, financial sustainability, and regional care. It puts a spotlight on the integration of standards, infrastructures, and users in the portal project, and on elements of collapsing networks that quietly resurfaced elsewhere. The reconstruction of these processes foregrounds different instances of repair work in the portal’s development and subsequent abandonment, repurposing, and erasure. Conceptually, this study contributes to academic debates in health information exchange, including the politics of technology, practices of participatory design, and the role of language in emerging information infrastructures. It latches on to ethnographic studies on information systems and infrastructural work, and brings together insights from actor-network theory, science and technology studies, and figurational sociology to rethink and extend current (reflexive and critical) understandings of technological development. It raises three questions: What work is done in the development and demise of an online health portal? How are relations between people and things shaped in that process? And how can insights from this study help us to understand changing sociotechnical figurations in health information exchange? The final analysis includes five key concepts: the act of building network extensions, the method of tracing phantom networks, the notion of sociotechnical figurations, the logic of plug-in healthcare, and repair as a heuristic device.

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)0.027
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0080.061
Scholarly communication0.0200.037
Open science0.0020.020
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.292
Teacher spread0.275 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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