Bibliographic record
Abstract
In this paper I look at the reasons for implementing VAR and the effect that it has had on the fans of soccer (football) in particular. I begin with a discussion of why VAR has been adopted in sports in general and in soccer specifically. I then discuss the notion of ‘flow sports’ and try to develop at taxonomy for classifying sports in terms of the relative importance of flow. Following this, I discuss the effect of VAR implementation on flow sports in general before examining the effect of VAR on the fan experience in soccer, a game which I characterize as one of the purist examples of team flow sports. Finally, I discuss the effect of VAR on the fan experience of flow when watching sports. My main contention is that VAR, at least in its current forms, represents an erosion of the flow experience in matches which impoverishes the fan experience. In light of the perceived benefits of VAR for match officiating, I doubt that it will be going away anytime soon. The best that we can hope for is that it evolves so as to cause minimal disruption to the flow in flow sports.
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 | 0.001 |
| 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".