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Record W3019824502 · doi:10.33151/ajp.17.787

The Structure and Characteristics of Anglo-American Paramedic Systems in Developed Countries: A Scoping Review Protocol

2020· review· en· W3019824502 on OpenAlexaff
Timothy Makrides, Linda Ross, Cameron Gosling, Peter O’Meara

Bibliographic record

VenueAustralasian Journal of Paramedicine · 2020
Typereview
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsIsland Health
Fundersnot available
KeywordsCINAHLGrey literatureMEDLINEData extractionInclusion (mineral)Corporate governanceProtocol (science)MedicineNarrativeMedical educationPsychologyPolitical scienceAlternative medicineManagementPathology

Abstract

fetched live from OpenAlex

Introduction Paramedicine has undergone significant change in the past two decades. While the Anglo-American paramedic system continues to grow there appears to be a dearth of published literature regarding modern categorisation of this evolving paramedic system. The objective of this scoping review is to examine and map the existing evidence to provide an overview of the characteristics and structural similarities and differences of Anglo-American paramedic systems in English-speaking developed countries. Methods Databases, including Embase, MEDLINE, Web of Science, EBSCOhost, CINAHL, Google Scholar and Epistemonikos, will be searched from inception. A grey literature search strategy has also been developed to identify non-indexed relevant literature. Citations and references of included studies will also be searched. Two reviewers will undertake title and abstract screening, followed by full text screening. Data extraction will be conducted using a customised instrument. Inclusion criteria: results examining management, leadership or governance in paramedicine related to the Anglo-American paramedic model in English-speaking developed countries will be included in the review. Included studies will be summarised using narrative synthesis structured around themes of management, leadership and governance in paramedicine.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.039
GPT teacher head0.399
Teacher spread0.360 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations9
Published2020
Admission routes1
Has abstractyes

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