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Record W1993307582 · doi:10.1136/ebn.9.1.7

Reflections on “Helping practitioners understand the contribution of qualitative research to evidence-based practice”

2006· letter· en· W1993307582 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

VenueEvidence-Based Nursing · 2006
Typeletter
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsQualitative researchPsychologyMedical educationEngineering ethicsSociologyMedicineEngineeringSocial science

Abstract

fetched live from OpenAlex

Although I congratulate Newman et al for bravely taking up the challenge that wading through the mire of qualitatively derived evidence entails, I find that their ultimate argument leaves me with more confusion than clarity. I fully agree with many of the excellent points they raise, but I would certainly take issue with others. However, reflecting on the thesis of their argument, I realise that the important conversation is not to argue the specific claims they make about qualitative research, its application, or its evaluation, but rather to examine the reasons that they are explaining these in the first place. Sometimes the greatest service a thoughtful paper can provide is sufficient discomfort to provoke further critical thinking. In that light, I hope that my response is understood as a beginning dialogue toward finding the clarity that we all aspire to within this complex, but ultimately fascinating, question. Newman et al have usefully articulated many of the current confusions and contradictions within the existing literature on what constitutes qualitative research, the criteria against which its quality can be determined, and the context within which its products can be reasonably taken up to inform clinical practice. They alert us to the taxonomy of methodological approaches that appear in our nursing literature (and the interdisciplinary literature upon which we draw) with regard to distinctions among and between these approaches and the manner in which they are actually applied. Quite rightly, they note that there are often far fewer distinctions between methods claiming to draw upon distinct approaches than would be anticipated. However, I would take issue with their conclusion that these methods are not all that dissimilar from one another after all. From my perspective, the problem is that none of these conventional qualitative methods were developed for quite the purposes that nurses …

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)0.045
metaresearch head score (Gemma)0.076
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.305
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0450.076
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0050.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.009
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 head0.714
GPT teacher head0.695
Teacher spread0.019 · 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