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Record W4415773865 · doi:10.1111/nin.70061

Visibility and Invisibility of Nurses in Hospital Settings: An Analysis Based on the Sociologies of Ignorance and of Absences

2025· article· en· W4415773865 on OpenAlexafffundabout
Évy Nazon, Caroline Dufour, Annie Rioux‐Dubois, Amélie Perron

Bibliographic record

VenueNursing Inquiry · 2025
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of OttawaUniversité du Québec en Outaouais
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInvisibilityVisibilityIgnoranceLegitimacyContext (archaeology)Thematic analysis

Abstract

fetched live from OpenAlex

Imbued with historical, cultural, and social aspects, nurses' visibility and invisibility have often been studied in terms of their work. Based on the sociology of ignorance and the sociology of absences, our aim in this article is to shed light on how organizational processes can actively produce nurses' visibility or invisibility on care units. To this end, we conducted an exploratory qualitative study with 15 nurses in three tertiary care hospitals that are part of a large health and social services center in Quebec, Canada. The data collected through semi-structured interviews, nonparticipatory observations, and analyses of patient records were subjected to thematic analysis. Three themes were identified from the analysis: the context of nurses' visibility, the impact of organizational structure on nurses' visibility and invisibility, and visibility associated with the persistence of the traditional image of the nurse. Hence, these themes help illustrate how organizational processes favor visibility and invisibility, and the instrumentalization of nurses. This is important to highlight these processes and denounce them so that the legitimacy of nurses' epistemic and political positions in healthcare settings is better considered.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.354
Teacher spread0.331 · 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.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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