The Strategies Sport Fans Used to Cope with the COVID-19 Pandemic Lockdown of Sporting Events
Bibliographic record
Abstract
When the COVID-19 pandemic shut down occurred, virtually all sports leagues—from recreational sports to professional leagues—were paused or canceled. This left a gap for fans of those sports to fill. The purpose of the present research study was threefold: 1) to examine what strategies sport fans used to cope with the loss of the live sport viewership/spectatorship; 2) determine how effective fans believed those coping mechanisms to be; and 3) examine fans’ behavioral intentions once sports were allowed to resume. Participants were recruited via a snowball sample and the Amazon MTurk platform. A total of 384 sport fans responded to the survey. While not all participants responded to all items, 168 indicated coping mechanisms for dealing with not watching sports and 219 reported coping mechanisms for not attending sports. The most common coping mechanism was watching old sporting events on television or via the internet. These mechanisms were reported to be very effective in helping participants cope with the loss of sports (M = 5.76, SD = 1.68 on a 1 to 8 scale). These findings provide support for the Team Identification – Social Psychological Health Model and suggest areas for interventions for sport marketers who are looking to maintain fans’ loyalty during future shutdowns of sport seasons, or other instances of missed sporting events.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".