Exploring the Information Source Preferences Among Canadian Adult Golf League Members
Bibliographic record
Abstract
With an aging demographic, and the abundance of physical inactivity in Canada, sport professionals need to understand how best to recruit and retain adults in sport and recreational activities, namely, golf leagues. Canadian golf league participants (N = 419; Mage = 62 years old) completed an online survey detailing their propensity to utilize a variety of information sources prior to making the decision to join a golf league. Results from a principal component analysis of a revised Information Sources Inventory, suggested that golfers in this sample were most likely to utilize Personal and Social sources of information associated with their league participation decision. While no differences emerged in information source preferences across Age or levels of Involvement, women (m = 4.12, SD = 1.30) were significantly more likely to utilize Public information sources than were men (m = 3.64, SD = 1.26). Implications from the information source preferences are discussed with the goal of generating more effective marketing strategies to recruit new golfers, lapsed golfers, or golfers who do not currently engage in league play.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".