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Record W2782212761 · doi:10.1177/1049732317750862

Body Mapping as a Youth Sexual Health Intervention and Data Collection Tool

2018· article· en· W2782212761 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQualitative Health Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsData collectionIntrospectionIntervention (counseling)Thematic analysisSocial connectednessPsychologyMedical educationApplied psychologyQualitative researchSocial psychologySociologyMedicineSocial science

Abstract

fetched live from OpenAlex

In this article, we describe and evaluate body mapping as (a) an arts-based activity within Fostering Open eXpression Among Youth (FOXY), an educational intervention targeting Northwest Territories (NWT) youth, and (b) a research data collection tool. Data included individual interviews with 41 female participants (aged 13-17 years) who attended FOXY body mapping workshops in six communities in 2013, field notes taken by the researcher during the workshops and interviews, and written reflections from seven FOXY facilitators on the body mapping process (from 2013 to 2016). Thematic analysis explored the utility of body mapping using a developmental evaluation methodology. The results show body mapping is an intervention tool that supports and encourages participant self-reflection, introspection, personal connectedness, and processing difficult emotions. Body mapping is also a data collection catalyst that enables trust and youth voice in research, reduces verbal communication barriers, and facilitates the collection of rich data regarding personal experiences.

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.

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)0.167
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1670.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.969
GPT teacher head0.830
Teacher spread0.139 · 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