Printed in Great Britain Healthy cities: Self-reliant cities
Bibliographic record
Abstract
Today the global village is the metaphor that informs our actions and guides our conduct. The world economy now depends on long distribution lines, major transportation subsidies, large-scale production systems and a separation of authority and responsi-bility. Every community becomes totally dependent on others as suppliers of its materials, products, capital and as recipients of its wastes. This residts in frag-mented, passive and unhealthy communities. A healthy city is a self-reliant city, capable of deter-mining its own future. The self-reliant city emphasizes holistic planning. Local self-reliance builds a self-confident and engaged citizenry while it strengthens local economies and protects the environment. Prevention, efficiency and the primacy of localism are the three governing principles of the self-reliant city. Health is a by-product of the way a community is organized and the way its members act. This is no longer a controversial statement. As one Canadian health study concluded, "Self-imposed risks, lifestyles and the environment are the prin-cipal or important factors in each of the five major causes of death between age one and age seventy... " (Lalonde, 1974). Dr John Knowles, then President of the Rockefeller Foundation observed, "Over 99 % of us are born healthy and made sick as a result of personal misbehaviour and environmental conditions " (1980). We know that lifestyles, the environment and the economy are leading causes of morbidity. One study notes that they are the leading con-tributing cause of death for 11 out of 14 major causes of death, from heart disease and cancer to motor vehicle accidents and suicides (Dever, 1972). Johns Hopkins University researchers have quantified the relationship between un-employment and child and wife abuse, suicide and alcoholism. We know that stress can cause not only peptic ulcers and high blood pressure This paper was prepared for the European Congress
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.347 | 0.146 |
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".