Supporting local communities of practice in sustainable supply chains: the case of Stocate in Montreal, Canada
Bibliographic record
Abstract
• The practices of decision-makers who support sustainable supply chains are researching, buying, selling, and managing, which are mutually beneficial and can be amplified by local communities of practice regarding sustainability (CoPS). • We codesigned and developed a support system for CoPS called Stocate, which operates as a social enterprise offering a knowledge mobilization platform and in-person services. • The system is designed to address 5 requirements: practical sustainability assessments, a pocket shopping assistant, a hybrid sales funnel, a collaborative platform, and a self-sustaining, agile, and scalable system. • Using the platform to share information and strengthen their collective impact, users have posted 3557 products, 336 businesses, and 1218 sustainability-related attributes. • Aligning decision makers' personal criteria (needs, values, preferences) with their impacts via sustainability assessments can lead to direct, collective action. Human society relies on its supply chains (SCs), which are in urgent need of a sustainable transformation – from the local to the global scale. However, coordinating on-the-ground efforts is obstructed by fragmented information, limited communications, and unreliable assessments, particularly at the local level. We demonstrate Stocate, a support system for local communities that practice sustainable consumption and production. Stocate was co-designed and developed with SC actors through a participatory action research approach in the city of Montreal, Canada. The result is a social enterprise offering both in-person services and an online platform (app and website). The platform synthesizes crowdsourced SC data into actionable insights aligned with sustainability assessments. By harnessing the platform to mobilize knowledge, Stocate helps decision-makers research, coordinate, buy, and sell sustainable products according to their needs, values, and preferences. By the end of the study, 390 users had posted 3612 products at 349 businesses along with 1889 sustainability-related attributes. Our findings suggest that empowering individuals to align their impacts with their personal criteria, and to collaborate in amplifying those impacts, can foster both direct and collective action. In this context, Stocate offers a socio-technological lever of change that transforms eco-anxiety into meaningful engagement toward a reformist circular society.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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".