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Record W2138043039 · doi:10.46743/2160-3715/2015.2115

Using Visual Vignettes: My Learning to Date

2015· article· en· W2138043039 on OpenAlexafffund
Tricia Morrison

Bibliographic record

VenueThe Qualitative Report · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health ResearchCanada Research ChairsOntario Society of Occupational Therapists
KeywordsVignetteStakeholderTerminologyNarrativePsychologyMedical educationPresentation (obstetrics)MedicineSocial psychologyPublic relations

Abstract

fetched live from OpenAlex

Cancer survivors report a gap in work integration advice from healthcare professionals. This occurs despite physicians routinely providing comment upon survivors’ work abilities to insurers and employers. In order to understand the phenomena of survivors’ work integration from physicians’ perspectives, a vignette methodology was used. Vignettes were chosen as a means to explore physicians’ perspectives in a non-confrontational and sensitive manner. Vignettes, composed of photographs and narratives reflective of survivors’ lived experiences of work integration were presented to 10 physicians during individual interviews. In this manuscript, I outline my experience using vignettes, the learning I have achieved, and the modifications I intend to make before again similarly using vignettes with another stakeholder group. In this study, receptive participants expressed enjoyment of the real-life nature of the vignettes through which significant insights into the phenomena were successfully gleaned. In this case, vignettes were an effective means to sensitively explore physicians’ perspectives of cancer survivors’ work integration. Yet, considerations that I will undertake prior to the next stakeholder inquiry include incorporating findings from the physicians and modifying the presentation of survivors’ findings to be more applicable to that next stakeholder, reconsidering the number of vignettes used as well as the terminology and delivery mechanism, and refinement of questioning format.

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)0.007
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.612
GPT teacher head0.679
Teacher spread0.067 · 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.

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

Citations3
Published2015
Admission routes2
Has abstractyes

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