Bibliographic record
Abstract
The aim of this paper is to explore how environmental practices contribute to the backpacker experience at hostels. Discovery of what environmental practices positively or negatively affect the backpacker experience will help when developing sustainable management strategies for hostels. There is a variety of material and academic studies regarding “green” tourism practices, however, to date, little research has been completed regarding the backpacker experience and environmental practices of hostels. The material presented in this literature review represents the backpacking experience on an international scale as well as important characteristics of sustainable tourism trends. \nThis applied research project used a mixed method approach including the use of quantitative and qualitative research measurements. The quantitative research helped to identify the positive and negative elements of the backpacker experience at hostels. Data collection for the qualitative research was completed through a semi-structured telephone interview with a sample size of four experts in sustainable practices and hostels. \nA key element for the data collection was the conceptual framework of the European Customer Satisfaction Model (ECSI) model. This model indicated how sustainable elements can influence the backpacker experience depending on the designated technical or functional purpose of the sustainable practice. The outcomes of the research including the finding that functional elements have a larger influence on the backpacker experience are presented in an adapted ECSI model. Additionally, the data produced a list of the critical success factors required for the implementation of sustainable practices at hostel location.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".