MétaCan
Menu
Back to cohort
Record W7058544596

Nursing and policy: nurses perspectives on ending hallway healthcare in Ontario

2022· dissertation· en· W7058544596 on OpenAlexaboutno aff

Bibliographic record

Venuee-scholar@UOIT (University of Ontario Institute of Technology) · 2022
Typedissertation
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careWork (physics)BureaucracyQualitative researchHealthcare policyFocus groupBridge (graph theory)Nursing care
DOInot available

Abstract

fetched live from OpenAlex

Drawing from elements of street-level bureaucracy this thesis examines the experiences and perspectives of six nurses (registered practical nurses and registered nurses) and their work with patients designated as alternate level of care (ALC) in an era within which policy initiatives include an end to hallway healthcare. Policies to end hallway healthcare focus on providing patients with the right care in the right location. Little attention has been focused on the impact of nursing on policy implementation. Using a descriptive qualitative approach, this study paid particular attention to the realities of everyday work in various hospitals throughout Ontario. The findings show that nurses have differing levels of awareness and understanding of policy. Further, they feel removed from policy planning and decision-making. This calls for attention of nursing institutions (education and workplace), professional associations, researchers and policymakers to help bridge this gap.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.626

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0340.018
Scholarly communication0.0090.003
Open science0.0010.005
Research integrity0.0030.004
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 head0.010
GPT teacher head0.235
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuee-scholar@UOIT (University of Ontario Institute of Technology)Same topicMagnetic Field Sensors TechniquesFrench-language works237,207