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Record W2257964071 · doi:10.11575/prism/13485

The intersecting social worlds of MRI scientists and MS clinicians

2004· dissertation· en· W2257964071 on OpenAlexaboutno aff
Julia Bickford

Bibliographic record

VenuePRISM (University of Calgary) · 2004
Typedissertation
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyData scienceMedicineComputer science

Abstract

fetched live from OpenAlex

Do basic scientists and clinicians represent two separate sub-cultures? In other words, if culture is defined from a cognitive perspective, do basic scientists and clinicians espouse similar beliefs and understandings about the objects and events in the world around them? What are the differences and similarities between scientists and clinicians? How do they relate to common objects? This research is a case study of basic scientists and clinicians working in the areas of Magnetic Resonance Imaging (MRI) and Multiple Sclerosis (MS) in a Western Canadian university hospital. Based on five months of qualitative and quantitative fieldwork, this study indicates that there are differences in how basic scientists and clinicians perceive five shared boundary objects: the MRI, the neurological patient, the CNS disease, neurological diagnosis, and the brain. This research also describes the social life of MRI as it passes through sub-cultures within a hospital organization.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.719

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 science0.0010.000
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 head0.034
GPT teacher head0.352
Teacher spread0.318 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2004
Admission routes1
Has abstractyes

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