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Record W2157880352 · doi:10.1111/nin.12033

Taken for granted: normalizing nurses' work in hospitals

2013· article· en· W2157880352 on OpenAlex
Ann‐Marie Urban

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.

Bibliographic record

VenueNursing Inquiry · 2013
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsWork (physics)IdeologyPower (physics)StaffingContext (archaeology)NursingSociologyPublic relationsMedicinePolitical sciencePoliticsLawHistory

Abstract

fetched live from OpenAlex

The aim of this article is to add to the research surrounding nurses' work in hospitals. Throughout history, nurses have faced adverse working conditions, an aspect of their work that remains remarkably unchanged today. Prevailing historical ideologies and sociopolitical conditions influences the context of nurses' work in contemporary hospitals. This research revealed how ruling patriarchal power and nurses' altruistic ways normalize the conditions in hospitals as nurses' work. Moving discourses further add to the work of nurses in hospitals. For example, cost containment strategies, overcapacity and short staffing have resulted in practices to accommodate these problems. While contemporary hospitals may look different, clearly, inside, little has changed since the early days; hospital issues have clearly become an ordinary part of nurses' work. This article discusses how the conditions in hospitals have become an ordinary part of nurses' work. The research in this article emphasizes how prevailing ideologies and institutional discourses make invisible and taken-for-granted, how this normalizing of nurses' work contributes to sustaining the hospital's power.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.333
Teacher spread0.301 · 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