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Record W2583990974

Much to do about nothing: the desertification of public health nursing practice in relationship to water and its impact on health

2014· dissertation· en· W2583990974 on OpenAlexaboutno aff
Penni L Wilson

Bibliographic record

VenueOpen ULeth Scholarship (OPUS) (University of Lethbridge) · 2014
Typedissertation
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsNothingPublic healthDesertificationNursing practiceNursingEnvironmental healthPolitical scienceEnvironmental planningPsychologyGeographyMedicinePhilosophyEpistemology
DOInot available

Abstract

fetched live from OpenAlex

The purposes of this phenomenological hermeneutics study were to gain an understanding of the meaning nine public health nurses (PHNs) in southern Alberta attach to their experience of promoting health related to safe and secure water; and to illuminate their emergent understanding of barriers and opportunities in that regard. Semi-structured interviews were conducted, and data analysis followed van Manen’s approach. Under an overarching theme, Being in the Desert, findings are presented through four themes: Desertification of the Practice Context; Desiccation of the PHN; Adaptation of the PHN; and Reclamation of Practice. Barriers to a role with water are central and embedded within the lived experience of PHNs; opportunities lie in the awareness that emerged through the discourse of the interviews. This discourse with PHNs must continue, so that they can begin to articulate an enhanced role in promoting health related to safe and secure water.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0130.028
Scholarly communication0.0060.003
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.133
GPT teacher head0.407
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2014
Admission routes1
Has abstractyes

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