MétaCan
Menu
Back to cohort
Record W4414240203 · doi:10.22329/cjpp.v3i1.8169

Moral Agency, Bureaucracy & Nurses: A Qualitative Study

2023· article· en· W4414240203 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Practical Philosophy · 2023
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsAgency (philosophy)Moral agencyMoral disengagementHierarchyQualitative researchBureaucracyHealth careQuality (philosophy)Distress

Abstract

fetched live from OpenAlex

This research explores moral agency among a group of nurses in an urban hospital located in a Western Canadian province. For this study, six Nurses were recruited and their stories describe various limitations within the culture of the healthcare system appears to constrict moral agency and possibly lead to moral distress among nurses. Moral agency seems to be influenced by hierarchy and taking initiatives, time/workload, and the “politics of healthcare”. Nurses also shared experiences of resiliency in facing moral dilemmas in the nursing profession. In conclusion, nurses appear to juggle conflicting priorities between providing quality care to patients and being efficient in the health system. As suggested by previous research, this climate leads to moral distress and may negatively influence the wellbeing of nurses in the care they provide to patients.

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.

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)0.017
metaresearch head score (Gemma)0.107
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.690
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.107
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.010
Insufficient payload (model declined to judge)0.0030.005

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 head0.395
GPT teacher head0.602
Teacher spread0.207 · 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