Health promotion by stealth: active transportation success in Helsinki, Finland
Bibliographic record
Abstract
The promotion of active transportation (AT-utilitarian trips including walking, cycling, and public transit use), represents a well-recognized opportunity for increasing physical activity. This study examines the strong AT success achieved in Helsinki, Finland (in 2013, the share of daily trips in Helsinki completed by AT was 77 per cent) from a political perspective. Helsinki represents a noteworthy example of AT success given important challenges including the region's relatively low population density, its difficult winter climate, and Finland's high driving rate. This research applied the advocacy coalition framework (ACF), a formal policy process theory from political science. Interviews were conducted with 23 AT experts in Helsinki. Document review was employed as a secondary method. Overall, the research indicates that Helsinki's success may be attributed to the long-term dominance of municipal transportation policy by a pro-AT advocacy coalition. When viewed from the perspective of health promotion, it is striking that this success is not strongly attributable to health considerations or efforts from health-related fields. Rather, the data suggest that the coalition, comprised of members from a variety of non-health fields, was most strongly motivated by a desire to protect a high degree of livability. Importantly, a number of significant historical events and background-level factors greatly facilitated success. Overall, these results suggest that health promotion advocates may have very useful allies in non-health sectors, and that awareness of the importance of political factors is likely to contribute to stronger health promotion efforts. Finally, several possibilities for related and further research are suggested.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".