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Record W2151900513 · doi:10.1177/0162243907306966

Displacement and Emplacement of Health Technology

2008· article· en· W2151900513 on OpenAlexaffabout
Pascale Lehoux, Blake Poland, Geneviève Daudelin, Dave Holmes, Gavin J. Andrews

Bibliographic record

VenueScience Technology & Human Values · 2008
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsUniversity of OttawaMcMaster UniversityUniversity of TorontoUniversité de Montréal
Fundersnot available
KeywordsUnit (ring theory)VideoconferencingSpace (punctuation)Public relationsHealth careIdentity (music)BusinessSociologyNursingMedicinePolitical scienceTelecommunicationsComputer sciencePsychologyLaw

Abstract

fetched live from OpenAlex

The provision of “closer-to-patient” services has increased in most industrialized countries. However, the migration of services in non-traditional health care settings implies redefining the role of technical and human entities and transforming the nature and use of technologies and places. Drawing on various scholarly efforts to conceptualize space, place, and technology, this paper compares and contrasts satellite and mobile dialysis units implemented in two regions in the province of Quebec, Canada. The satellite units were hosted in two small, local hospitals where nursing staff had been recently trained. The mobile unit was a bus adapted to host five dialysis stations; nurses traveled back and forth between a university teaching hospital and two sites located within a radius of 7.6 miles. In both projects, nephrologists supervised from a distance via a videoconferencing system. Our aim is to illustrate the ways in which the displacement of technical and human entities gives shape to new forms of emplacement in non-traditional health care settings. The satellite and mobile units contributed to the culture of dialysis care and transformed the identity of nurses, doctors, patients, and technologies. By contrasting two projects involving different spatial and clinical logics, we analyze in what ways certain forms of recombination of human and technical entities can prove incomplete but nevertheless acceptable to providers and project managers.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaScience and technology studies
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptScience and technology studies
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.008
metaresearch head score (Gemma)0.011
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.051
Scholarly communication0.0100.006
Open science0.0010.014
Research integrity0.0020.002
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 head0.106
GPT teacher head0.489
Teacher spread0.383 · 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

Labeled directly by 2 models reading the full record.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical · Other

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

Citations14
Published2008
Admission routes2
Has abstractyes

Explore more

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