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Record W4295709210 · doi:10.1136/ip-2022-044619

Transforming injury prevention for youth (TrIPY): an intersectionality model for youth injury prevention

2022· article· en· W4295709210 on OpenAlexaffabout
Alyssa Miles, Brandy Tanenbaum, Shari Thompson-Ricci

Bibliographic record

VenueInjury Prevention · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsUniversity of TorontoHealth Sciences CentreBrock UniversitySunnybrook Health Science Centre
Fundersnot available
KeywordsIntersectionalityPoison controlSuicide preventionInjury preventionPublic healthOccupational safety and healthMedicinePsychologyNursingSociologyEnvironmental healthGender studies

Abstract

fetched live from OpenAlex

Injury is deadly and expensive, and rates are increasing. The cost of injury is not only a financial burden; individuals, families and communities suffer the human costs of physical and emotional injury. For children and youth in Canada, injuries are the leading cause of death and disability. However, the risk of preventable injury is not equal for all youth. The transforming injury prevention for youth (TrIPY) model aims to recognise and remediate these inequities by applying an intersectionality lens to injury prevention programming. TrIPY conceptualises injury prevention programming through an intersectionality lens. The model was developed with diverse youth in mind, and the intended users include injury prevention practitioners, partners, stakeholders, communities and decision-makers. TrIPY was designed using a transformative perspective and built on core concepts within public health, injury prevention, intersectionality, gender analysis, youth risk, health equity, and systems of privilege and oppression. TrIPY helps to analyse intersecting inequities along multiple dimensions, to improve injury prevention programmes for diverse youth with unique identities, skills and lived experiences. The end goal of implementing an intersectionality model within injury prevention is to find out who is being missed in order to address existing inequities concerning youth injury. No matter what a person's unique social location or lived experience, they will have the opportunity to be included in prevention programming. Developing injury prevention programmes through an intersectionality lens is needed to better understand the factors that interact to influence an individual's risk for injury. There is a need to explore the unique experiences of youth at the intersection of various identity factors, including gender, race and ethnicity, and socioeconomic status. With this knowledge, prevention programmes can be more culturally responsive, gender transformative, inclusive, accessible and engaging for diverse groups of youth.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.293
Teacher spread0.244 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2022
Admission routes2
Has abstractyes

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