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Record W2944782719 · doi:10.1017/s1049023x19003637

The Problems on Your Desk: A Research Study to Define and Describe Paramedic Practice in Canada

2019· article· en· W2944782719 on OpenAlexaboutno aff
Ron Bowles

Bibliographic record

VenuePrehospital and Disaster Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)DeskStakeholderPsychologyMedicineKnowledge managementComputer sciencePublic relationsPolitical science

Abstract

fetched live from OpenAlex

Introduction: Paramedicine is a rapidly evolving profession, growing from its initial role of providing emergency care and transportation of the sick and injured into a broad discipline providing a wide range of care in multiple practice settings, yet the field is relatively unexplored. Much of the research in the field centers on patient care, often from the perspective of emergency medicine. A growing body of literature describing the discipline itself is largely descriptive. Aim: This interactive presentation describes and contributes to an applied research project that will define and describe Canadian paramedic practice. The research will develop frameworks, common taxonomy and designs, and evidence to support development of a national Canadian Paramedic Information System. Methods: This two-year mixed methods study is gathering data from a literature review, stakeholder workshops, and key informant interviews. The project will develop “user cases” that explore the issues and challenges facing Canadian paramedic stakeholders and identify the information and data required to address those issues. Results: The presentation will present initial findings that describe core concepts, data/knowledge structures, and models that are foundational to understanding and informing current and emerging paramedic practice. It will explore this data in relation to operational needs of practitioners, operations, communities, and stakeholders to inform decision-making, guiding policy and direction, and advancing the profession. Lastly, it will develop explanatory principles, models, and relationships in a conceptual framework that describes paramedic practice. Discussion: The study will develop models and core data sets that guide research and support policy development at local and national levels, and inform operational and strategic decision-making. The presentation will provide an overview of the research and findings to date. Participants will engage in activities that explore the user-cases and selected findings, applying the results of the study through the lens of their own backgrounds and operational contexts.

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)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.150
Threshold uncertainty score0.986

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0280.008
Scholarly communication0.0070.003
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.346
Teacher spread0.303 · 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 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

Citations1
Published2019
Admission routes1
Has abstractyes

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