Residential areas and civil aviation airport location criteria.
Bibliographic record
Abstract
A major concern of community planning is with the social implications for people of the integration of the uses of space. One of the implications of this is the examination of the impact of the various uses of space on residential communities. In the past seventy years, civil aviation has grown to where airports require large amounts of space. As a major facility, the airport has a definite and distinctive impact on proximate residential communities. Airport location as dictated by two basic kinds of factors, those of physical ground and airspace requirements and the relationship to residential areas were examined. The solution to the second problem is currently to avoid these areas. This, however, neglects the problem of the impact of the airport on existing proximate residential areas. To put the problem in perspective the basic physical and airspace requirements were examined. To examine the second problem the following hypothesis was developed:- The proximity of a civil aviation airport significantly lowers the environmental quality of a residential area. There are two components to the hypothesis, that of the subjective view which residents take of the airport, and an examination of the facility from a residential point of view. The term "environmental quality" which is normative was operationalized in terms of five characteristics of the airport. 1) Aircraft Noise. 2) Air pollution from aircraft. 3) Non-occupant aircraft crash hazards. 4) Location of industry attracted by the airport. 5) Ground vehicle traffic. Each of these characteristics was examined to determine what its impact is on a residential area. Following this an attitude survey of Berkeville, a residential community located immediately adjacent to the Vancouver International Airport was undertaken to determine the residents attitudes to each of the five characteristics. Data on the socio-economic characteristics of the residents of Berkeville was also gathered, and questions directed to the reasons for moving to and staying in the area. Using the multivariate contingency tabulations program (MVTAB) socio-economic characteristics were correlated with the attitudes to each characteristic. The major conclusions of the thesis are that:- 1) The proximity of the airport results in a decline in the environmental quality of Berkeville. This is largely a function of aircraft noise and air pollution. These two characteristics create conditions for an area in constant transition. 2) Occupation, age, and length of resident were the most important and consistent indicators of attitudes to the five characteristics, but that the attitudes are in many cases generalized regardless of socio-economic characteristics. 3) The negative attitudes to non-occupant crash hazards, which constitute a small risk to the residents, can be traced to the areas'high population turnover, a situation which is linked to aircraft noise and aircraft air pollution. 4) The residents perceived quite clearly that the ground traffic problem had decreased over time. 5) The airport industrial area (excluding ground traffic) had little negative impact on Berkeville. 6) Attenuation of the aircraft noise and air pollution problems at the source is the only long-term solution to the problem. In the interim, residential areas and airports should be separated. , Attenuation of these two characteristics at the source, the maintenance of present airport zoning, separation of ground traffic, and central location of airport industry would result in compatibility of the airport and residential uses.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".