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Record W2746261470 · doi:10.1111/jocn.14014

Examining the social construction of surveillance: A critical issue for health visitors and public health nurses working with mothers and children

2017· review· en· W2746261470 on OpenAlexaffabout
Sue Peckover, Megan Aston

Bibliographic record

VenueJournal of Clinical Nursing · 2017
Typereview
Languageen
FieldMedicine
TopicData-Driven Disease Surveillance
Canadian institutionsDalhousie University
FundersMenzies Centre for Australian Studies, King's College London, University of LondonAmicus Therapeutics
KeywordsMeaning (existential)Privilege (computing)Context (archaeology)Public healthHealth careNursingPublic relationsSociologyPsychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

AIMS AND OBJECTIVES: To critically examine surveillance practices of health visitors (HV) in the UK and public health nurses (PHNs) in Canada. BACKGROUND: The practice and meaning of surveillance shifts and changes depending on the context and intent of relationships between mothers and HVs or PHNs. DESIGN: We present the context and practice of HVs in the UK and PHNs in Canada and provide a comprehensive literature review regarding surveillance of mothers within public health systems. We then present our critique of the meaning and practice of surveillance across different settings. METHODS: Concepts from Foucault and discourse analysis are used to critically examine and discuss the meaning of surveillance. RESULTS: Surveillance is a complex concept that shifts meaning and is socially and institutionally constructed through relations of power. CONCLUSIONS: Healthcare providers need to understand the different meanings and practices associated with surveillance to effectively inform practice. RELEVANCE TO CLINICAL PRACTICE: Healthcare providers should be aware of how their positions of expert and privilege within healthcare systems affect relationships with mothers. A more comprehensive understanding of personal, social and institutional aspects of surveillance will provide opportunities to reflect upon and change practices that are supportive of mothers and their families.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.218
GPT teacher head0.531
Teacher spread0.312 · 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 designOther design
Domainnot available
GenreReview

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

Citations22
Published2017
Admission routes2
Has abstractyes

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