The effects on residential opportunity structures on participation patterns in voluntary organizations
Bibliographic record
Abstract
The major focus of this investigation is to explore two alternative models of individual-environment articulation for explaining individual participation in voluntary organizations. The primary question posed is whether varying voluntary organizational opportunity densities of local residential areas operate to encourage organizational participation to the same degree for all residents; or whether the density of organizational opportunity elicits differential participation depending upon an individual's personal resources, or attachments to the local residential area. The development and analysis of the problem is informed by the theory and methods of "contextual analysis." The hypotheses were tested with data from 822 respondents randomly selected from eight different "social areas" in Metropolitan Vancouver. The areas were purposively chosen from a stratified typology—similar in nature to Wendall Bell's Social Area Typology. In general, the analysis suggests that the opportunity densities of a residential areas do not act independently of, but in combination with different individual characteristics to produce differences in organizational participation of urban residents. Increased organizational opportunities present in the immediate residential environment only conditionally affect an increase in organizational memberships for the better educated or the more wealthy.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 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".