Mega-event volunteers, similar or different? Vancouver 2010 vs London 2012
Bibliographic record
Abstract
Purpose – The purpose of this paper is to compare motivations of volunteers at two mega multi-sport events. Design/methodology/approach – The research used a quantitative research design to survey volunteers at the Vancouver 2010 Olympic and Paralympic Winter Games ( n =2,066) and the London 2012 Olympic and Paralympic Games ( n =11,451) via an online questionnaire based upon the Special Event Volunteer Motivation Scale. Findings – The results indicate that the volunteers, most of whom had previously volunteered, were motivated by similar variables, including the uniqueness of the event, the desire to make it a success and to give back to their community. The results of the principal components analysis indicated that most items of the scale loaded onto similar components across the two research contexts. Research limitations/implications – There were methodological limitations in terms of the timing of the questionnaire administration and Likert scales used, however, these issues were controlled by gatekeepers. These limitations could have research implication for comparative studies of volunteers at mega events. Practical implications – Understanding volunteer motivations will enable event managers and volunteer managers to plan for legacy. Social implications – Volunteer motivations include wanting to give back to their community and therefore, increases the potential for volunteer legacy. Originality/value – This is the first research that: enables comparison of winter and summer Olympic and Paralympic Games volunteers; has substantial sample sizes in relation to the variables; applies higher item loadings to strengthen the analysis; and involves the use of the same instrument across events.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".