Bibliographic record
Abstract
Purpose The purpose of this paper is to develop both a systematic framework and priorities for comparative and cross‐cultural festival management studies, based on literature review and results of a four‐country study. Design/methodology/approach This research is based on four samples of festivals in Sweden, Norway, UK, and Australia that are systematically compared. The survey is designed to profile the festivals in terms of vision/mandate, ownership, age, size, assets, venues used, decision‐making structure, and programs. Costs and revenues are examined in some detail, including trends in each category. Festivals' use of volunteers and sponsors are specifically addressed. Levels of dependence on a number of types of stakeholders and other strategic management issues are also explored. Respondents are also asked to respond to statements regarding challenges and threats to their festival and organization. Findings The empirical research identifies important similarities and differences that exist within the UK, Sweden, Norway, and Australia, by three ownership types, in how festivals are organized, their operations and strategies, stakeholder influences and dependencies, threats, and strategies. Research limitations/implications In the recommended framework are five components: antecedents; planning and management; planned event experiences and meanings; outcomes and the impacted and dynamic patterns; and processes. Specific points of comparison are enumerated within each component, foundation theories and concepts are identified, and some research priorities suggested for each. Originality/value The framework developed in this paper can help advance both the process and applications of comparative festival studies.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".