Bibliographic record
Abstract
We golfBrian grew up a few blocks from a nine-hole golf course in a small city in Ontario, Canada -and spent many an afternoon, evening, and sometimes night (i.e.junior hours) playing rounds, chipping, and putting on greens long-abandoned by those who had completed their rounds.Brian vaguely remembers friends who joked that you should "not lick your golf balls" because they would be coated with the chemicals that were sprayed on the course.Brad played golf in the Ontario suburbs as much as possible too.Golf was and remains a social activity as much as a sporting endeavour -a reason to spend time with family and friends.The site of lush greens and fairways was a sign that winter had thawed.We both grew up enamoured with the pristine courses we saw on television.Brian's parents took him to see the Canadian Open golf tournament at Glen Abbey Golf Club in Oakville, Ontario in the early 1980s, where he saw Jack Nicklaus, Greg Norman and others manoeuvre a golf course that Brian remembers as a utopian landscape -with fairways that looked like putting greens, and putting greens that looked like billiard tables.Brad's memories of golf are tied as much to watching tournaments such as the Masters on TV as they are to experiences actually playing the game.Golf is a game we both grew up with, and one we genuinely enjoy and appreciate.We have golfed together many times.We tell you this at the outset because this book, and the research and arguments that are featured within it, unsettled how we see the game of golf.Specifically, this work raised serious questions for us about golf 's evolving relationship with the environment, and how various stakeholders in golf have responded to pressing environmental concerns.By raising these questions in the pages that follow, we might be seen by some as social scientists (i.e.critics) who don't like and don't 'know' golf.This couldn't be further from the truth.However, as social scientists who are ultimately interested in and concerned with the factors that influence those who make decisions that have important consequences for public health and the health of the world's natural environments we feel obligated to tell the story that emerged from our research into golf 's environmental history -and its environmental present.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".