MétaCan
Menu
← Back to cohort
Record W4243218376 · doi:10.1163/9781848881075_007

Providing a Creative Space for Expression: I.D. VIDEO, a Video-Art Pilot Project for Immigrant Youth

2012· book-chapter· en· W4243218376 on OpenAlexaboutno aff
Néomée Alain, Joanna Empain, Winny Ang

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsVisionFace (sociological concept)The artsSpace (punctuation)Expression (computer science)Visual artsSociologyPsychologyArtComputer scienceSocial science

Abstract

fetched live from OpenAlex

Upon their arrival to a new country, immigrant youth face many social, economic and personal challenges, noticeably a break with their social network and cultural references, and a shift in self-perception. In response to this issue, I.D. VIDEO, was developed, building upon the school-based, creative arts prevention programs developed by Dr. Rousseau’s transcultural psychiatry team at McGill University. I.D. VIDEO’s goal was to provide a safe and playful space for expression in order for immigrant youth in several ‘welcoming classes’ in Montréal (Canada) to explore their common past and present experiences. The youth viewed artist’s videos and learned basic camera techniques as inspiration to create their visions that challenged traditional media forms and reflected their multiple perspectives. Cultural strengths and collective losses occurring due to migration were addressed through the creative use of video technology, with the hope of providing a place for elaborating flexible identities so as to better face the discrimination that often accompanies the acculturation to a new country. School based creative projects, such as I.D. VIDEO might be one way of highlighting assets, developing talents and facilitating solidarities among marginalized individuals and communities.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.140
GPT teacher head0.323
Teacher spread0.182 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicCultural Industries and Urban Development→French-language works237,207→