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Record W3019786499 · doi:10.1891/crnr-d-20-00003

Design Thinking in Nursing Education to Improve Care for Lesbian, Gay, Bisexual, Transgender, Queer, Intersex and Two-Spirit People

2020· article· en· W3019786499 on OpenAlexafffund
Erin Ziegler, Benjamin Carroll, Chris Shortall

Bibliographic record

VenueCreative Nursing · 2020
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsQueen's UniversityToronto Metropolitan University
FundersInstitute of Gender and HealthCanadian Institutes of Health Research
KeywordsQueerTransgenderLesbianDesign thinkingNursingHealth careSociologyPsychologyGender studiesMedicineComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Design thinking methodology is a collaborative strategy with the potential to create innovations. Design thinking is being used increasingly in health care. Design jams are interdisciplinary events that bring together experts and community members to collaborate on creative solutions to health-care problems. This article describes the design thinking process and includes reflection on the authors' participation in a design jam event aimed to address the knowledge-to-action gap that exists in health care for (LGBTQI2S) people.

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)0.056
metaresearch head score (Gemma)0.043
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.295

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0560.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0070.021
Scholarly communication0.0120.007
Open science0.0020.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.098
GPT teacher head0.419
Teacher spread0.321 · 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

Citations17
Published2020
Admission routes2
Has abstractyes

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