Bibliographic record
Abstract
The main focus of this paper is on a training program for telephone skills that was conducted at the end of January 2019 in a local hotel in Jordan. Depending on the philosophy of this study, choosing a qualitative investigation is appropriate because it examines the informers' position of behaviours and experiences being studied (Dawson, 2002). The research suggests that a limited amount of training program evaluation has a limited impact on performance improvements. A case-study approach was conducted in this evaluation. Besides, the data used for this study is primary in nature, as it reflects the participants' observations (Saunders, Lewis, and Thornhill, 2007) and is based on the subjective qualitative research approach (Greener, 2008). The data collected were based on interviews taken from ten employees and the human resources manager (HRM) of the hotel. According to HRM view, it has been found that the telephone skills training program did have an impact of change mainly on the front office employees. Furthermore, it has been found that training has a sustainable effect and was a motivation by itself for the employees. However, learning processes which were addressed in literature were not considered in this program. Therefore, limited impact on performance and culture was identified. This evaluation attempt is an introduction for future research associated with training programs within the local hotel industry in Jordan.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".