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Record W2106517270 · doi:10.1136/emj.2008.059048

Introduction to the "space-control theory of paramedic scene management"

2009· article· en· W2106517270 on OpenAlexaff
Anthony Campeau

Bibliographic record

VenueEmergency Medicine Journal · 2009
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsMinistry of Health and Long Term Care
Fundersnot available
KeywordsMedicineSpace (punctuation)Medical emergencyControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Scene management is a critically important aspect of paramedic practice but, to date, there has been no formal research in this area. OBJECTIVE: To generate a substantive theory of paramedic scene management practice. METHOD: A grounded theory methodology was used to conduct a qualitative inquiry that involved interviewing paramedics concerning their approach to scene management. Paramedics were selected from rural, suburban and urban settings and were categorised by competence level as novice, experienced and expert. RESULTS: A theory was generated that describes how paramedics coordinate key specific social processes to establish "space control" at the scene. CONCLUSION: This study introduces the first formal theory of paramedic scene management and suggests that recognition of this aspect of practice will improve both pre- and in-service educational programming and assist with medical quality assurance.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.021
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.073
GPT teacher head0.478
Teacher spread0.406 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations40
Published2009
Admission routes1
Has abstractyes

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