Enabling “barrio” innovation: a grassroots approach for centering community initiatives in just sustainability transformations
Bibliographic record
Abstract
Sustainability transformations are most meaningful when communities take ownership of their collective futures and guide transformative processes that are rooted in their local traditions and value systems. Yet, researcher–community collaborations aimed at facilitating meaningful transformations can fall short of their objectives if they do not explicitly recognize bottom-up transformative processes that already exist in the community that enable grassroots ways of knowing and addressing sustainability challenges prevalent in the community. This paper addresses this gap in researcher–community partnerships by illustrating a transdisciplinary collaboration that emerged among researchers, educators, and advocates in South Phoenix, Arizona that sought to center recognitional and epistemic justice from the start. These collaborations led to the co-designing and execution of school curriculums in three learning centers in South Phoenix aimed at developing researcher capabilities among learners for exploring the pasts, presents, and futures, and contributing to transformative action in their community. This paper outlines the approaches that this group of collaborators, who are all co-authors in the paper, took toward forming reciprocal relationships and facilitating just transformations in the community. First, we describe our collaboration process, which was mindful of activating existing spaces of community leadership as well as cultivating spaces of reciprocal knowledge exchange and reflection among the collaborators. Next, we outline our approach toward facilitating just transformations, which we call “barrio” innovation, which is based on principles of embracing a mindframe of abundance, enabling transformative pathways, and focusing on the micro-scale. We further illustrate, through case studies, how our approaches to collaborations and transformations manifested in different learning centers and with different collaborators in South Phoenix. We conclude with our collective reflections and the practices that worked for us toward facilitating just transformations through meaningful researcher–community collaborations.
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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 | 0.022 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.043 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".