Exploring the expectations and satisfaction derived from volunteer tourism experiences
Bibliographic record
Abstract
The aim of this paper was to examine the satisfaction of voluntourists derived from various aspects of their trip. Framed within the Existence, Relatedness and Growth Theory, the paper examines volunteers’ motivations, expectations and satisfaction based on their financial and time investment volunteering with Volunteer Eco Students Abroad (VESA), the intereactions they had on the trip, and the extent to which travellers felt as though they contributed to community goals. In 2012, the researchers carried out in-depth, semi-structured interviews with 16 Canadian voluntourists following their time in St. Lucia, South Africa. A thematic analysis was used to interpret the data, resulting in three themes: ‘Evaluating Investment’, ‘Contribution to Community’ and ‘Opportunities and Reaffirmations’; sub-themes were matched with aspects of Existence, Relatedness and Growth Theory. Findings elicited several levels of expectations of voluntourists revealed through their feelings of satisfaction or dissatisfaction. On the lowest level, voluntourists expect adequate food and water whilst volunteering. Informants highlighted the various ways they raised fund for the trip, and this impacted their level of accountability for contributing to the community. Volunteers also expect volunteer organizations to be transparent regarding the use of funds and expressed dissatisfaction when this did not occur. Volunteers anticipated a feeling of connection between the hosts and themselves and were frustrated if they felt more time could have been allotted to working with community residents. Lastly, informants expected the experience to provide an opportunity for self-learning and professional development and overall were satisfied with this element of the trip.
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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 | 0.004 | 0.011 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".