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Record W4388999612 · doi:10.1177/23333936231212281

Phenomenographic Approaches in Research About Nursing

2023· article· en· W4388999612 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsQueen's University
FundersGöteborgs Universitet
KeywordsPhenomenographyPhenomenology (philosophy)NursingInclusion (mineral)PhenomenonNursing practicePsychologyMedicinePedagogyEpistemologySocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

We propose that phenomenography is well-suited to research about nursing, given its focus on identifying variation in individuals' experiences, and inclusion of diverse voices and perspectives. Phenomenography explores qualitatively different ways in which a group of people experience a phenomenon, often using semi-structured interviews. The use of phenomenography is especially relevant in research about nursing which provides accounts of the experiences of nurses and patients within complex practice settings. We consider the tenets of phenomenography and examine phenomenography's relationship to and differences from phenomenology. We review literature published about phenomenographic research in nursing and reflect on the potential benefits of phenomenographic research about nursing. This paper adds to knowledge about use of phenomenography in research about nursing.

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.

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)0.065
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.615
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0650.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.020
Science and technology studies0.0030.007
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.748
GPT teacher head0.710
Teacher spread0.037 · 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