Natural to artificial: a spectrum of sport spaces fit for the Anthropocene
Bibliographic record
Abstract
Over time, sport has progressively moved indoors and toward more controlled environments, a set of related processes dubbed ‘artificialisation’ and ‘indoorisation’. This has mirrored broader anthropocentric changes in society globally. In reflecting on the evolving relationship between sport and the natural environment, and the shifts in who and what is considered in the production and reproduction of sport practices, we use MacInnis’ method of delineation to advance the Natural to Artificial Spectrum as an invitation to have more nuanced conversations surrounding sport’s relationship to the natural world. The implications of a sport practice’s placement on the spectrum – and its shifts along the spectrum over time and across geographic space – span across participant health and wellbeing, sport experiences, competitiveness and alignment with international (largely Western) standards, environmental attitudes and behaviours, participation and maintenance costs, environmental impacts, and climate vulnerability.
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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 | 0.000 | 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".