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Record W7070933578

Public health nurses' perceptions of duty during an influenza pandemic : a qualitative study / by Janice Tigert Walters.

2017· dissertation· en· W7070933578 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typedissertation
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthGovernment (linguistics)PandemicContext (archaeology)PretextHealth care
DOInot available

Abstract

fetched live from OpenAlex

For this study, a grounded theory qualitative design was used to explore public health nurses? perceptions of their professional duty to care during a severe influenza pandemic or an infectious disease outbreak where there would be some degree of personal risk. This study examined their underlying personal values, beliefs and morals as well as their professional ethics and understanding of a duty to care. This research
\nwas specifically interested in the conflicts they anticipated experiencing between their personal female care-giving roles and family responsibilities (female identity) and their professional nursing obligations (professional identity). 
\nA purposeful sample of twenty-two public health nurses from five Ontario health units were interviewed using an open-ended semi-structured questionnaire. A theoretical framework was developed from the prevalent themes that emerged during the data analysis. A grounded theory is offered for how public health nurses develop their self-identity from a core, female and professional identity and how their self-identity can ?reassort? over the course of their lives based on situational influences. The self-identity that is dominant in a nurse at the time of a public health crisis will affect her perception of duty. Public health nurses will be significant human health care resources during a severe influenza pandemic or any public health crisis involving an infectious disease. This study offers important information on identity construction for employers,
\ngovernments and policy makers to consider as they plan for future pandemics or other outbreaks to ensure the strongest public health nursing response when needed.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.174
GPT teacher head0.464
Teacher spread0.289 · 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 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
Published2017
Admission routes1
Has abstractyes

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