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Record W3192710342 · doi:10.13162/hro-ors.v9i1.4510

The Regulatory Amalgamation for Nursing and Midwifery in British Columbia

2021· article· en· W3192710342 on OpenAlexaffvenueabout
Kathleen Leslie, Angela Freeman, Ivy Lynn Bourgeault

Bibliographic record

VenueHealth Reform Observer - Observatoire des Réformes de Santé · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsUniversity of OttawaUniversity of WaterlooUniversity of VictoriaAthabasca University
Fundersnot available
KeywordsMandateGovernment (linguistics)PacePublic administrationPolitical scienceControl (management)NursingPublic relationsMedicineManagementLawEconomicsGeography

Abstract

fetched live from OpenAlex

On 1 September 2020, Canada's first combined nursing-midwifery regulator was created with the amalgamation of the separate nurse and midwife regulators in British Columbia (BC). The highly critical Cayton Report on health profession regulation, the previous experience of amalgamating nursing regulators in BC, and a broader call for more efficient and effective regulation were factors influencing this reform. The goals of the reform were to increase regulatory efficiency (by maximizing economies of scale) and effectiveness (by ensuring adequate resources to meet the public interest mandate) and, for the regulators, to control the pace and progress of the amalgamation ahead of impending government dictate. These goals of the regulators' proposal to amalgamate clearly fit with the BC government's vision for modernizing health profession regulation. To implement the amalgamation, the BC government released an Order in Council on 8 June 2020 that amended various regulations under BC's Health Professions Act and confirmed the September 1 date of amalgamation. There is currently no clearly articulated evaluation plan for this reform; however, evaluating regulatory efficiency and effectiveness in the interests of the public is likely to be a focus moving forward for both regulators and governments.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0050.000
Scholarly communication0.0000.001
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 head0.061
GPT teacher head0.413
Teacher spread0.351 · 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 designObservational
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
Published2021
Admission routes3
Has abstractyes

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