Donner une voix aux Inuits urbains: "Photovoice" comme une pratique de multilittératie dans la construction d’identité et de savoirs transfrontaliers
Bibliographic record
Abstract
Résumé Cet article présente des résultats d’un projet de recherche ethnographique et collaboratif s’intéressant aux pratiques multimodales de littératie auprès de la communauté Inuit urbaine à Ottawa. Conçue comme un projet de recherche-action l’étude a été menée par des chercheurs universitaires en collaboration avec le programme de littératie familiale attaché au centre d’enfants Inuit à Ottawa (OICC). Cette recherche porte sur la méthode « Photovoice » et sa mise en pratique dans le contexte de la communauté Inuit urbaine. Notre recherche poursuit deux objectifs. Le premier consiste à explorer la façon dont « Photovoice » a été appropriée par la communauté Inuit urbaine comme un moyen de stimuler la réflexion sur l’expérience de migration transfrontalière et la création d’identités Inuit urbaines. Le deuxième cherche à reconnaître la méthode « Photovoice » comme une pratique sociale de littératie et à évaluer sa place comme méthodologie de recherche au sein des New Literacy Studies. Nos résultats de recherche suggérons que « Photovoice » en tant que méthode promouvant la multilittératie peut servir d’outil de réflexion et d’apprentissage dans le contexte communautaire des Inuits urbains ainsi que dans d’autres contextes. This paper reports on a collaborative, action-based research project exploring multimodal literacy practices among urban Inuit in Ottawa. Working in the context of the family literacy program of the Ottawa Inuit Children’s centre, we examine two “Photovoice” activities conducted by Inuit children, youth, and adults in 2009 and 2010. The goals of this examination are twofold: 1) to explore “Photovoice” as a multimodal literacy activity, and its appropriation by urban Inuit as a means to creatively explore, reflect upon, and represent aspects of urban Inuit identity and experiences; and 2) to situate “Photovoice” methodologically and theoretically in the realm of New Literacy Studies, which sees literacy as a social and cultural practice, rather than a set of discrete linguistic skills to be taught, learnt, and acquired. In this way, “Photovoice”, drawing on the visual, oral, and scriptural modes, is seen as an ideal type of literacy activity in community-based educative contexts, such as urban Inuit in Ottawa, with wider application across contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".