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Record W2142950465 · doi:10.1145/2559206.2581302

Supporting non-verbal visual communication in online group art therapy

2014· article· en· W2142950465 on OpenAlexaff
Brennan Jones, Sara Prins Hankinson, Kate Collie, Anthony Tang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsBC Cancer AgencyAlberta Cancer FoundationUniversity of Calgary
Fundersnot available
KeywordsArt therapyPsychologyComputer scienceNonverbal communicationMultimediaPsychotherapistHuman–computer interactionCommunication

Abstract

fetched live from OpenAlex

Art therapy provides therapeutic benefit to people suffering from chronic pain, and recent work has explored supporting art therapy through online tools such as chat forums and discussion boards. These tools give people the benefit of engaging in art therapy without the burden of having to leave one's home (when transportation may be a challenge), and allowing people to reveal their identities through dialogue and activity rather than through one's appearance. However, these tools also do not provide much opportunity for collaboration and shared art making. Because group members are not aware of each other's actions and non-verbal cues in a chat room, they cannot collaborate with each other easily. We discuss the design and development of tools that promote enhanced awareness of non-verbal cues and shared creative experiences in online group art therapy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0020.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.035
GPT teacher head0.336
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2014
Admission routes1
Has abstractyes

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