Reconnaître, valoriser et transmettre - Les Ateliers Design et culture matérielle en Territorie Guarani (Brésil): Une Pédagogie Hybride entre Art, Artisanat et Design pour le Développement de Vecteurs de Transmission Culturellement Signifiants
Bibliographic record
Abstract
Résumé: Ce projet, débuté en 2008 à Sapukai, communauté guaranie de l’État de Rio de Janeiro, implique un partenariat entre trois associations guaranies, regroupant les membres de cinq communautés, la section de l’état de Rio de Janeiro de la Fondation nationale de l'Indien (Funai) et le Museu do Indio de Rio de Janeiro. Les recherches menées dans le cadre du projet Design et culture matérielle : développement communautaire et cultures autochtones ont servi de cadre de référence pour la création du programme du projet mené par La Boîte Rouge vif5. Par le biais d’un inventaire culturel communautaire et d’ateliers de formation en vidéo, photographie, techniques d’entrevue, design graphique et design d’exposition, les treize participants guaranis ont travaillé à identifier, à scénariser et à diffuser des éléments culturels qu’ils considéraient importants à transmettre aux générations futures. Notre partenariat auprès de ces cinq communautés s’est poursuivi jusqu’en juillet 2012 par des activités d’évaluation participatives et de produits de médiums de diffusion. Dans cet article, nous ferons un survol des principales actions menées en 2008, ainsi qu’un commentaire sur leur validité en regard des objectifs du programme. Abstract: This project, which started in 2008 in Sapukai, a Guarani community located in the state of Rio de Janeiro, Brazil, was a partnership with 3 Guarani associations, members of 5 Guarani communities, as well as with FUNAI and Museu do Índio. Researches undergone within Design and material culture: community development and indigenous cultures inspired a specific program to reflect on methodologies developed in Canada. From a community cultural inventory, carried out through trainings in photography, film making, interview techniques, graphic, and exhibition design, thirteen Guarani participants identified, scripted and communicated cultural elements they thought important to transmit to future generations. Our partnership with these five Guarani communities continued with participative evaluations and the production of cultural expression projects until July 2012. This article is mainly about the actions our group went on in the introductory work carried out in the field.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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.
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".