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Record W2022996432 · doi:10.13162/hro-ors.01.01.02

Assessing Ontario's Personal Support Worker Registry

2013· article· fr· W2022996432 on OpenAlexaffvenueabout
Audrey Laporte, David Rudoler

Bibliographic record

VenueHealth Reform Observer - Observatoire des Réformes de Santé · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBusinessPsychology

Abstract

fetched live from OpenAlex

In response to the growing role of personal support workers (PSWs) in the delivery of health care services to Ontarians, the Ontario government has moved forward with the creation of a PSW registry. This registry will be mandatory for all PSWs employed by publicly funded health care employers, and has the stated objectives of better highlighting the work that PSWs do in Ontario, providing a platform for PSWs and employers to more easily access the labour market, and to provide government with information for human resources planning. In this paper we consider the factors that brought the creation of a PSW registry onto the Ontario government’s policy agenda, discuss how the registry is being implemented, and provide an analysis of the strengths and weaknesses of this policy change. Prenant acte du rôle de plus en plus important joué par les préposés aux services de soutien à la personne (PSSP) dans les soins fournis aux Ontariens, le gouvernement de l’Ontario a décidé de créer un registre des PSSP. L’inscription dans ce registre sera obligatoire pour tout PSSP travaillant pour des employeurs financés sur fonds publics et les objectifs suivants sont poursuivis : mettre en valeur le travail des PSSP en Ontario, fournir un point d’accès au marché du travail pour les PSSP et leurs employeurs, et fournir au gouvernement l’information nécessaire pour planifier les ressources humaines dans ce domaine. Dans cet article, nous décrivons les facteurs expliquant comment la décision politique de créer un registre des PSSP a été prise, nous discutons la façon dont celui-ci est mis en place, et nous proposons une analyse des forces et limites de cette décision politique.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.002
Scholarly communication0.0010.006
Open science0.0010.000
Research integrity0.0010.002
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 head0.130
GPT teacher head0.386
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2013
Admission routes3
Has abstractyes

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