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Record W1816094117 · doi:10.33151/ajp.6.2.451

Why Paramedics Require “Theories-Of-Practice”

2008· article· en· W1816094117 on OpenAlexaff
Anthony Campeau

Bibliographic record

VenueAustralasian Journal of Paramedicine · 2008
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsMinistry of Health and Long Term Care
Fundersnot available
KeywordsPsychological interventionIdentification (biology)Perspective (graphical)Health careMedicineValue (mathematics)Medical educationNursingPsychologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

This article discusses the role of Theories-of-Practice for health care professionals and specifically focuses on the need for such theories in the paramedic profession. Key benefits to the development of paramedic theory include occupational differentiation and self-awareness, and identification of appropriate research topics. Almost all paramedic research, training and practice are focused on specific patient care assessments and interventions. A quick perusal of any Emergency Medical Service or prehospital care journal will reveal an impressive list of research articles that are focused on demonstrating the value (or absence thereof) of patient care procedures. This is important work, and indeed such research is required in order to appropriately define the medical aspects of paramedics’ scopes-of-practice. However, there is an equally important need to research and develop theory about the whole practice of paramedicine as a profession. This perspective is different from narrowly focusing on discrete, technical patient care interventions, because it seeks to define the occupation more comprehensively, inclusive of all types of professional knowledge. When considering professional matters such as these, one cannot avoid comparisons to other professions and the interest in such theories among other health professions has been variable.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.443
Teacher spread0.379 · 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.

Study designNot applicable
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

Citations13
Published2008
Admission routes1
Has abstractyes

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