Bibliographic record
Abstract
Purpose The purpose of this paper is to present the key food experience factors that affect a consumer’s restaurant meal enjoyment. It considers the effects on the dining experience that come from enhancements in today’s restaurants and the advent of the foodie customer. The paper reviews the modern restaurant scene in Canada and how best practices have created non-events despite differentiation attempts among producers of hospitality experiences. Design/methodology/approach In this paper, the literature regarding current practices in modern restaurants is reviewed, along with a discussion of the foodie consumer. Analysis draws on the theory that many transactions in hospitality are mundane and few offer meta-hospitality memorable moments. Findings With the expanding range of restaurant choice across Canada – serving better-than-ever food options in green environments in unique servicescapes – it would appear that these are the golden years of the food service industry. Yet the reality could be that consumers are walking away feeling that all gastronomic experiences are equally mundane. Practical implications An examination of the way we approach food service as entertainment and escape is called for. Examining hospitality trends is part of what makes the industry a source of fascination for consumers and researchers. Originality/value The author’s culinary background as a professional chef and his recent academic experience, including his doctoral research in a related topic, enriches the originality of this article.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".