Identifying Competencies for Leisure and Hospitality Curriculum in a Rural Region
Bibliographic record
Abstract
This case study describes how competencies that are common across entities that operate in the leisure and hospitality industry in North Central Idaho were identified. The leisure and hospitality industry is crucial to the economy of many rural regions with scenic surroundings. Tourists’ satisfaction, however, depends on their experiences with frontline staff in the industry and service encounters are among the significant factors for customer satisfaction. Developing curriculum that leads to the proper training of frontline customer service representatives is important. A groupware process using workers in the leisure and hospitality sector was used to identify duties, tasks, general knowledge, skills, and attitudes for a guest relations agent. Issues and future trends were also identified. Results show half of the duties referenced essential interaction with customers, such as communicating to support customers and team, providing customer service, providing product/service/organization information, and providing customer assistance for local and regional activities. Trends and issues also point to the need to be prepared for factors such as outbreak of disease that may affect the operations in the sector.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".