Exposing a lack of communication regarding sport policy: An analysis of the Canadian talent identification process
Bibliographic record
Abstract
The Sports Policy Factors Leading to International Sporting Success (SPLISS), a comparative high performance and elite sport (HPS) model, has identified nine distinct pillars that contribute to the success of a country’s HPS system. The study was originally conducted in 2003 with seven nations from Europe and North America. Beginning in 2009, the study was repeated and expanded to include 17 nations from North America, South America, Europe, Asia, and Oceania. While the SPLISS study was designed to examine and compare countries’ HPS systems, the aim of this research is to compare the intra-country results of Canadian athletes, coaches, and performance directors with the goal of exposing communication and perception issues of the three groups to one environment.\nQuantitative data was obtained through surveys (online and word document) and telephone interviews between September 2011 to May 2012. 11 coaches, eight performance directors and 161 athletes completed the survey. The low number of respondents in the performance director and coach groups limited possible quantitative analysis methods, due to reliability and validity. However, the existence of the SPLISS framework provided direction for descriptive analysis by comparing responses towards each pillar for each survey group.\nWithin pillar four (talent identification and development) and pillar five (athletic and post-career support), descriptive analysis revealed interesting discrepancies regarding the viewpoints of the different groups. In one specific example, the athletes believe they were identified as elite athletes by the national governing body between the ages of 16 to 18, whereas six out of eight performance directors noted athletes were identified as an elite athlete below or at the age of 13. Amongst coaches, there was no clear consensus of an age category with answers ranging from 11 to 25. However, seven coaches expressed that the identified age was too late. The lack of consistent recognition between the groups on the actual HPS identification age may indicate a communication problem within the talent identification process. It is possible that athletes are being identified without knowing it. Talent identification is an important step in the development of HPS athletes, yet it appears the process of identification is unclear to the athlete. This is just one example of differed understanding towards sport policy and the presentation will outline other areas where a lack of communication may be present. Increased effective communication between stakeholder groups may assist with the creation, clarification, and implementation of sport policy.
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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 | 0.016 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".