MétaCan
Menu
Back to cohort
Record W2804237667 · doi:10.3138/chr.99.2.01

The Second “Great Transformation”: Renegotiating Nursing Practice in Ontario, 1945–70

2018· article· en· W2804237667 on OpenAlexvenueaboutno aff
Peter L. Twohig

Bibliographic record

VenueCanadian Historical Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsNursingNursing AssistantCertificationNurse educationNursing shortageTeam nursingMedicineEconomic shortageNursing researchPolitical scienceNursing homesGovernment (linguistics)

Abstract

fetched live from OpenAlex

In the period following the Second World War, hospitals in Ontario faced a shortage of nurses that prompted the renegotiation of nursing practice. This article examines the introduction of “certified” nursing assistants, a new category of worker who became the fastest-growing segment of the nursing labour force. Nursing assistants occupied an important position in the reorganization of nursing labour in these years, intentionally positioned between registered nurses and a pool of other support workers, such as practical nurses and ward aides. Nursing assistant training programs were established throughout Ontario and helped to create a credentialed community of practice. From 1946 to 1959, 4,840 nursing assistants were registered in Ontario. Between 1960 and 1966, more than 12,000 nursing assistants were registered, increasing to 17,723 in the final three years of the 1960s. The rapid growth of nursing assistants reveals the extent by which nursing labour in Ontario was reorganized in these years. Importantly, registered nurses were not mere bystanders in this transformation but, rather, effectively managed the critical issue of encroachment, at least for the short term. The system of registration created in Ontario effectively legitimated the participation of registered nurses in the regulation of nursing assistants. Registered nurses also participated in important ways in the governance of nursing assistants, in overseeing education programs, and in supervising the clinical work done by nursing assistants. Finally, the shift toward recognizing “registered nursing assistants” acknowledged that nursing labour was undergoing segmentation, with tasks being divided among different kinds of workers.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.265
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.277
Teacher spread0.251 · 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
GenreOther

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

Citations7
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Historical ReviewSame topicCanadian Identity and HistoryFrench-language works237,207