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Record W2002617728 · doi:10.1177/0898010110376323

Finding a Balance

2010· article· en· W2002617728 on OpenAlexaffabout
Kaysi Eastlick Kushner, Margaret J. Harrison

Bibliographic record

VenueJournal of Holistic Nursing · 2010
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGrounded theoryIdeologyBalance (ability)InstitutionSocial psychologyPsychologyAction (physics)Process (computing)SociologyPublic relationsApplied psychologyNursingMedicineQualitative researchComputer sciencePolitical scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

PURPOSE: We investigated how mothers employed in support staff positions make personal and family health decisions. DESIGN: We used a critical feminist grounded theory design. METHODS: Twenty women employed at a large Canadian institution participated over two years in repeat interactive interviews. FINDINGS: "Finding a balance" was the emergent core process of health decision making in response to the basic social problem of multiple demands and uncoordinated, sometimes conflicting ideologies. Women emphasized recursive movement within a continuous process of four action phases: cueing in, figuring out, generating solutions, and assessing results. Two distinct views of finding a balance were revealed: weighing competing interests or harmonizing multiple interests. These distinctive views contributed to variation in women's approaches to decision making and to their personal and family health experiences. CONCLUSIONS: Women's experiences suggest a capacity for reflective practice in health decision making that provides an excellent basis for holistic, emancipatory nursing practice.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.034
GPT teacher head0.360
Teacher spread0.326 · 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 designNot applicable
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

Citations4
Published2010
Admission routes2
Has abstractyes

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