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Record W1975724815 · doi:10.1177/1354067x14551293

Scaffolding one Thai youth’s drawing toward resilience

2014· article· en· W1975724815 on OpenAlexaff
Catherine Ann Cameron, Giuliana Pinto, Sombat Tapanya

Bibliographic record

VenueCulture & Psychology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThrivingPsychological resilienceContext (archaeology)Inclusion (mineral)PsychosocialVisual artsPsychologySociologyGender studiesAestheticsSocial psychologyArtHistoryArchaeologySocial science

Abstract

fetched live from OpenAlex

Drawings have been used extensively to explore the psychosocial development of children and youth. Focusing on the drawings of one thriving migrant Thai adolescent, this case study employs multiple sources of data from this youth to ground an integrated interpretation of his resilient processes in ecological context. Our participant, ‘Pond’, had recently relocated to northern Thailand with his father. Employing reflective interviews with the teenager about his experiences, his sketchbooks and a filmed ‘ day in his life,’ we identified ‘promotive’ factors contributing to his well-being in the context of strong familial support. During his filmed day, we observed him drawing for one uninterrupted hour, the products of which he proudly shared with his artist father as well as the researchers. His sketchbook graphic endeavors included traditional Thai representations, pop-cultural sketches and cartooning, bridging the worlds he navigates as he adapts to his new domicile. Pond’s drawing activities and reflections on them confirm his sense of responsibility, self-confidence, positive affect in familial connection and his striving for social inclusion. His use of pictorial language reveals his cultural values and their potential for enhanced thriving. Pond affirmed that his artistic transactions are sources of strength to him in his migratory transition.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.734
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

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

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 head0.053
GPT teacher head0.365
Teacher spread0.312 · 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 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

Citations9
Published2014
Admission routes1
Has abstractyes

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