MétaCan
Menu
Back to cohort
Record W2801444931 · doi:10.1386/jaah.9.1.53_1

A modified Delphi study on research priorities in cancer, gender and the arts

2018· article· en· W2801444931 on OpenAlexaff
Chad Hammond, Roanne Thomas, Stéphanie Saunders, Lorraine Holtslander, Ryan Hamilton

Bibliographic record

VenueJournal of Applied Arts and Health · 2018
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of New BrunswickUniversity of SaskatchewanUniversity of Ottawa
Fundersnot available
KeywordsThe artsDelphi methodNegotiationPsychological interventionPanel discussionDelphiPsychologyPublic relationsMedical educationPolitical scienceMedicineSociologySocial scienceNursing

Abstract

fetched live from OpenAlex

Abstract Men and women diagnosed with cancer may encounter complex changes to gendered roles and expectations within the work environment, families and the community. Creative interventions using the arts could address some of these challenges using person-centred approaches that attend to gender disruptions and negotiations. To identify current research gaps and future priorities in this field, a national expert panel was assembled of seventeen professionals in cancer and gender research, supportive cancer care and artistic practice. During a two-day forum, the panel participated in a modified Delphi process involving two rounds of surveys, a breakout session and panel discussions. At the end of the forum, the panel had identified three diverse programmes of research highlighting key areas at the intersection of cancer, gender and the arts. This process showed both the need for and the promise of interdisciplinary collaborations to identify creative research solutions for gendered challenges during health crises.

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)0.088
metaresearch head score (Gemma)0.072
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 score0.088
Threshold uncertainty score0.466

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0880.072
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0120.006
Scholarly communication0.0050.004
Open science0.0020.011
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.300
GPT teacher head0.502
Teacher spread0.202 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Arts and HealthSame topicEmpathy and Medical EducationFrench-language works237,207