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Record W6888490601 · doi:10.20381/ruor-27953

Development and usability testing of tools to facilitate incorporating intersectionality in knowledge translation

2022· other· en· W6888490601 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Ottawa - Library · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityPluralistic walkthroughIntersectionalitySystem usability scaleUsability engineeringEquity (law)Cognitive walkthroughIntervention (counseling)

Abstract

fetched live from OpenAlex

Abstract Background The field of knowledge translation (KT) has been criticized for neglecting contextual and social considerations that influence health equity. Intersectionality, a concept introduced by Black feminist scholars, emphasizes how human experience is shaped by combinations of social factors (e.g., ethnicity, gender) embedded in systemic power structures. Its use has the potential to advance equity considerations in KT. Our objective was to develop and conduct usability testing of tools to support integrating intersectionality in KT through three key phases of KT: identifying the gap; assessing barriers to knowledge use; and selecting, tailoring, and implementing interventions. Methods We used an integrated KT approach and assembled an interdisciplinary development committee who drafted tools. We used a mixed methods approach for usability testing with KT intervention developers that included semi-structured interviews and the System Usability Scale (SUS). We calculated an average SUS score for each tool. We coded interview data using the framework method focusing on actionable feedback. The development committee used the feedback to revise tools, which were formatted by a graphic designer. Results Nine people working in Canada joined the development committee. They drafted an intersectionality primer and one tool that included recommendations, activities, reflection prompts, and resources for each of the three implementation phases. Thirty-one KT intervention developers from three countries participated in usability testing. They suggested the tools to be shorter, contain more visualizations, and use less jargon. Average SUS scores of the draft tools ranged between 60 and 78/100. The development committee revised and shortened all tools, and added two, one-page summary documents. The final toolkit included six documents. Conclusions We developed and evaluated tools to help embed intersectionality considerations in KT. These tools go beyond recommending the use of intersectionality to providing practical guidance on how to do this. Future work should develop guidance for enhancing social justice in intersectionality-enhanced KT.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.797
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.103
GPT teacher head0.234
Teacher spread0.131 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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