Bibliographic record
Abstract
Coffee attraction experiences: A narrative studyRefl ecting a rich global coff ee culture this paper explores the experience of visitors to coff ee attractions as refl ected through travel narratives published in the coff ee trade literature.It fi rst positions coff ee related tourism within culinary tourism and then examines the types of attractions related to coff ee.Using a typology of coff ee attractions derived from the literature on both attractions and coff ee travel narratives from fi ve specialized coff ee periodicals are reviewed.In doing so the paper makes a dual contribution to both furthering the study of attractions related to coff ee tourism and to using narrative study methods in tourism research.In particular it is suggested that the narrative methodology may be applied to the study of other sectors of culinary tourism.A limitation of this study however is the use of secondary sources mainly derived from the coff ee specialist literature.Nonetheless the narratives reveal the rich coff ee culture and coff ee experiences that can be associated with coff ee related travel.In addition this exploratory study using published coff ee narratives indicates the potential for future research investigating on a fi rst hand basis the coff ee experiences of tourists.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.042 | 0.016 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.004 | 0.010 |
| 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".