Reduce, Reuse, Refill: Understanding the Refill-based Sector in Ontario
Bibliographic record
Abstract
As a reuse-based system, refills offer a starting point in reducing packaging waste and shifting our capitalist, linear economies towards more circular approaches. The concept of ‘refilling’ has been present since the advent of milk delivery services (Vaughan et al., 2007), however the study of what a refill is, and how it works in practice, is insufficiently understood. The purpose of my research is to fill this gap in understanding by investigating the motivations and challenges faced by retailers who offer refills of household and personal care products in a case study of Ontario. This qualitative study involved one-on-one, semi-structured interviews (n=23) with refill-based retailers across Ontario. Key findings include challenges such as customer education and recruitment, COVID-19 and having to ‘do it all alone’, and motivations, including environmental motivations. The implications of this study reveal that further research is needed on the accessibility of refills, and their economic and environmental viability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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 teacher head, 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".