Doing Design Research with Youth at/from the Margins in Pandemic Times: Challenges, Inequalities and Possibilities
Bibliographic record
Abstract
Context: SEEYouth project SEEYouth is a research project about youth from/at the margins carried out by an international group of scholars from the University of São Paulo and the University of the State of São Paulo (both in Brazil), University of Lapland (Finland), University of Leeds (United Kingdom) and Université de Montreal (Canada). Focusing on how to improve vulnerable youths’ and young adults’ lives, this project aims to use artsbased and design methods to give voice and help them to empower themselves through trans-Atlantic mirroring cases from Brazil and Finland. To be held from January 2020 until December 2021, the SEEYouth project suffered a deep impact in its very first months, when the covid-19 pandemic crisis started worldwide. In Brazil, the first case was confirmed on 26 February 2020, in São Paulo. The kick-off research meeting was planned to be held in Finland by the end of March, but due to restrictions imposed by the pandemic, the country closed its borders in the second week of the month. In Brazil, social isolation was determined at the same time. Thus, since its beginning, all research meetings have been carried out online through Skype® for group meetings and Miro® for visual collaboration in a digital whiteboard. COOPAMARE Led by the University of São Paulo research team, the SEEYouth Work Package 1 focuses on former homeless young adults’ history of life that could inspire the youth from/at the margins in Finland. These adults improved their lives by working at a cooperative called COOPAMARE [ Cooperativa dos Catadores Autônomos de Papel, Aparas e Materiais Reaproveitáveis (Cooperative of Paper, Scrap and Reusable Materials Autonomous Pickers, in a loose translation)], which we will explain briefly. In Brazil, it is estimated that over 220,000 people are homeless (Natalino, 2020). In São Paulo alone, there are nearly 25,000 people living on the streets (SECOM, 2020). Most of them do not have access to drinking water, sanitation, nutrition, health care or education. The city is also facing new challenges with the increasing number of immigrants and refugees living on the streets. COOPAMARE is the oldest and most relevant operating waste pickers association in Brazil. It has achieved international recognition for its experience in the field of solid waste management and advocating for the rights of populations in a state of social vulnerability.
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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 | 0.067 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".