Canadian Sustainable Fashion Micro And Small Enterprises: Navigating The Sustainable Development Goals Through Online Marketing
Bibliographic record
Abstract
Sustainability within the fashion industry is a complex topic. With increasing consumer concern about the social, economic, and environmental impacts of the products they purchase, the industry must take action to transform the existing fashion system. The 17 Sustainable Development Goals (SDGs) were introduced by the United Nations in 2015, who have identified both the fashion industry and micro and small enterprises as key players in fulfilling the goals. This research examines 40 micro and small Canadian sustainable fashion businesses through observation of their Instagram content and websites, and semi-structured interviews. Through a thematic analysis, the data was studied to determine which SDGs these businesses align with, and the best practices for them to incorporate the goals. Results reveal that the SDGs are a strong tool for relaying a business’ sustainability initiatives to their consumers, and that all of the businesses studied align with at least two of the goals. Keywords: MSEs, sustainable development, SDGs, Global Goals, marketing, sustainable fashion marketing, branding, Canadian fashion, Canadian small business, small businesses, transparency, entrepreneurship, decade of delivery
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".