Bibliographic record
Abstract
Issue addressed: Transport systems have recently been identified as significant social determinants of health. Because physical activity is extraordinarily effective in protecting physical and mental health, health professionals are beginning to promote 'active transport' (travel by foot, bicycle or public transport) as a sustainable positive lifestyle habit. This paper argues that a convergence of interests in health, environment protection and transport is opportune for securing more livable neighbourhoods and better public health. This paper takes a composite ecological approach to investigating the links between transport, environment and health, rather than the conventional pollution paradigm. In doing this, three issues are raised: the scale of the health damaging effects of current and projected transport practices; the potential for increasing the health promoting effects of transport; and the potential to intervene in practical ways in the harmful trend toward sedentary car travel at the expense of active transport. Conclusions: Health promotion professionals implementing the full range of health promotion actions outlined in the World Health Organization's Ottawa Charter could advance and support the movement for health linked transport practices and policies in Australia. So what?: Achieving healthier transport systems will take time but the benefits for health and quality of life will be considerable. (author abstract)
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".