The effect of spatial layout and social similarity on urban neighbouring
Bibliographic record
Abstract
This thesis presents a detailed study of the effect of functional distance and social similarity on the greetings and visits between contiguous neighbours. Functional distance is predicted to have an inverse relation with greetings while social similarity is predicted to have a direct relation with visiting between contiguous neighbours. In accordance with previous researchers, functional distance is predicted to have an inverse relation with visiting only for socially similar, but not for socially dissimilar, neighbours. Women, whose single family houses are located throughout metropolitan Vancouver, were interviewed in the summer months. Similarity in six characteristics, which were employed separately, in specific combinations, and all together, was determined for each respondent-contiguous neighbour pair. This pair was the unit of analysis. Somers' d was used to test the direction and strength of the relationships. A calculation of Goodman and Kruskal's gamma substantiated the deductions which were based on Somers' d values. It was found that these contiguous neighbours tend not to have any form of contact with each other. The functional distance between neighbour pairs was found, as predicted, to be consistently negatively related to greetings while their similarity was consistently positively related to visiting. Functional distance was negatively, and more strongly, related to casual visiting for similar rather than dissimilar pairs, but the strength of its association with planned visiting was the same regardless of similarity. Some limitations of this research are outlined with suggestions for improvements in future endeavours in this area.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".