Specialization versus diversification in the event portfolios of amateur athletes
Bibliographic record
Abstract
This study explores the personal event portfolios of amateur athletes, differentiating between those who pursue a specialized career within one sport and those who diversify within multiple sports. The impetus for this paper was the observation made in previously published research that many sport-event tourists participate in multiple sports. The twin objectives of the study are to better understand highly involved participants and to draw implications that could contribute to the events’ and the country's competitiveness in sport event tourism. The study also addresses the question of whether or not these portfolio choices emerge as involvement increases – in other words, do highly involved amateur athletes tend to specialize in one sport, as suggest by recreation specialization theory? A total of 6691 participants were surveyed online in five events (cross-country run, Nordic ski, half-marathon run, open-water swim, and road cycling), out of which 2329 were identified as pursuing a portfolio strategy. The major contributions of this paper include identification of a large number of significant differences between “specialized” and “diversified” portfolios. Planning and marketing implications that can potentially enhance the attractiveness of individual and collectively marketed events are also discussed.
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".