Examining the outcomes of sport specialization for individual athletes and the industry
Bibliographic record
Abstract
In North America, sport specialization for young athletes has become a prerequisite for sport achievement, but academics have yet to explore the effects that sport specialization has on athletes’ consumption and participation patterns. Thus, this project explores the following research question: what are the effects of sport specialization on the individual volleyball athlete in terms of: i) patterns of participation in sport (past, present, and future); and ii) consumption patterns in the sport industry? The methodological approach was to interview current and retired volleyball players aged 18 to 30 in Calgary, Alberta. The questions were designed to ask participants how they spend their time and money during and after sport specialization. The findings indicate that early specialization in volleyball directly impacts an athlete’s patterns of participation and consumption in the sport of volleyball and the sport industry broadly. Many participants articulated that due to specialized training they became lost in the identity of a “volleyball player,” and when they ceased participation in the sport they found that they had not been participating for their own intrinsic values but for extrinsic values placed on them by their coaches, parents, teammates, and other invested stakeholders. Participants also indicated that their specialization years developed specialized knowledge in sport, a unique analytical consumption experience that influences present and future sport consumption. The findings are a call to action for the volleyball industry to evaluate the participation and consumption patterns in specialized volleyball training and implement changes to benefit specialized athletes and the industry.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".