Assessing the current sustainability initiatives of Canadian SME restaurants
Bibliographic record
Abstract
Purpose The purpose of this study is to investigate what sustainability initiatives are being implemented by Canadian independent restaurants and to determine if the initiatives represent all 10 categories of a sustainable restaurant as established by a sustainability initiative framework. Design/methodology/approach The study uses a qualitative approach of semi-structured interviews with 15 small to medium enterprise (SME), independent restaurant owners and operators across Canada. The data was digitally transcribed and thematic analysis was performed. Findings Results indicated that most initiatives aligned with the categories of “sustainable food/menu” and “waste reduction and disposables” which shows that the operators were inclined to pursue initiatives in customer view. Restaurants put limited focus on water supply, chemicals and pollution reduction, furniture and construction materials. Some of the barriers to implementing, measuring and learning about initiatives were: cost, lack of access to programs, supply chain complications, not having buy-in from owners and lack of time to implement. Practical implications The study recommends that governments provide incentives to implement sustainability initiatives that are out of sight to the customer. For example, implementing composting, energy efficient equipment and water saving processes. It is also recommended that third-party restaurant organizations provide more accurate, evidence-based guidance and education on implementing a wide-range of sustainability initiatives. Originality/value This research contributes to the literature on sustainability in restaurants and applies a sustainability initiative framework in a practical context. The study provides a unique assessment of the current state of restaurant sustainability and states where restaurants need to improve their efforts.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".