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Record W2996877658

Photonovels Through Critical Pedagogy

2009· book· en· W2996877658 on OpenAlexaboutno aff
Laura Nimmon

Bibliographic record

VenueVDM Verlag Dr. Müller eBooks · 2009
Typebook
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsParticipatory action researchEthnographyCitizen journalismImmigrationPedagogyFluencyLiteracyPopulationSociologyGender studiesPublic relationsPsychologyPolitical scienceAnthropologyMathematics education
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this research was to study how the process of creating and using a participatory photonovel can empower ESL speaking immigrant women and act as a tool to educate them about a health topic. Conducted at the Intercultural Association of Greater Victoria, under a critical ethnographic paradigm, this study involved five ESL speaking immigrant women from various cultural, national and linguistic backgrounds with different degrees of fluency in English. The women named nutrition and exercise as being their most pressing health concern upon migration to Canada. The women then created a participatory photonovel entitled From Junk Food to Healthy Eating:Tanya’s Journey to a Better Life. The author found that the photonovel was an effective and culturally relevant health literacy tool to use with this population. Results also illustrated that the participatory process created community and helped the women raise their consciousness about nutrition in Canada. This study was awarded a Canadian Population and Public Health Masters Research Award and was shortlisted for the Language and Literacy Researchers of Canada Masters Research Award.

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)0.006
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 score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.016
Scholarly communication0.0070.007
Open science0.0020.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0130.002

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 head0.598
GPT teacher head0.650
Teacher spread0.053 · 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
Published2009
Admission routes1
Has abstractyes

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