Golf's Environmental Message: Old News or New? Now is not the time to be complacent with golf's environmental issues.
Bibliographic record
Abstract
'GOlf courses are good for the environment. " "Golf's guide to environmental stewardship." "Environmental commitment on the golf course. " How many times have you heard these types of statements over the past 15 years? Be that as it may, environ-mental awareness and activism is not old news; it will remain a core issue for the golf industry for decades to come. Safeguarding environmental quality should continue to be a primary goal of the golf industry. Yet, too often, Green Section staff members hear golf course officials and staff comment, "We're doing all of that " or "It's time to move on to a new issue " or ''I'm tired of hearing about IPM. " More subtly, they watch a person's eyes glaze over at the mention of environmental issues. Although research studies demonstrate that proper turf grass management does not threaten environmental quality, as an industry we cannot afford to claim victory too early.Without due diligence when making day-to-day management decisions and continually communicat-ing the responsible efforts taken to care for the environment, the golf industry is only one misapplication away from receiving a black eye and finding itself scrambling to improve its environ-mental image yet again. Pesticide and water issues alone should be enough motivation to con-vince superintendents and course officials that the golf industry needs to remain actively involved in environ-mental stewardship. These topics will loom on the horizon for many years. Several communities throughout the United States and beyond are lobbying 4 GREEN SECTION RECORD for the elimination of all synthetic pesticide and fertilizer use on turf areas, including golf courses. In 2002, the Supreme Court of Canada ruled that municipalities were allowed to ban the use of lawn pesticides. In 2004, legisla-tion in Suffolk County, N.Y, proposed to ban the cosmetic use of pesticides by homeowners and lawn care operators.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.091 | 0.058 |
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; both teacher heads agree on what is shown here.
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".