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Record W236565724

Using visual methods to capture embedded processes of resilience for youth across cultures and contexts.

2010· article· en· W236565724 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

VenuePubMed · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsDalhousie University
Fundersnot available
KeywordsReflexivityPsychological resiliencePsychosocialArgument (complex analysis)PsychologyNegotiationField (mathematics)Process (computing)Power (physics)Social psychologyDevelopmental psychologySociologyComputer scienceSocial sciencePsychotherapist
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: We review the value of using visual data in a dialogue with youth, to reflect, explore and find language to better understand processes of resilience. METHODS: The argument is demonstrated with examples from the Negotiating Resilience Project (NRP): an international study of 16 youth which uses video recording a day in the life of youth participants, photographs produced by youth, and reflective interviews with the youth about their visual data. RESULTS: Three examples from the NRP are used to show the ways that visual methods can capture and elucidate previously hidden aspects of youth's positive psychosocial development in stressful social ecologies. CONCLUSION: Incorporating images as research data can aid in understanding previously unarticulated constructions of youth resilience. When the researcher is reflexive about power dynamics and their role in co-constructing the research environment, visual methods have the potential to reduce power imbalances in the field, meaningfully engage youth in the research process, and help to overcome language barriers.

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)0.007
metaresearch head score (Gemma)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.487
GPT teacher head0.666
Teacher spread0.180 · 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