Population turnaround in inner city Winnipeg, 1981-1986
Bibliographic record
Abstract
This dissertation explores the process of population turnaround in Winnipeg's inner city in the 1981-1986 period. Population turnaround is the stabilization of, or increase in, population after a period of decline. Drawing from various theoretical insights that have been used to explain inner city change, the study explores the demographic and socio-economic changes accompanying turnaround, the local factors and conditions that underlay turnaround, and the culture of turnaround in terms of the reasons, rationales and factors influencing residential choice. The study employs quantitative and qualitative methods including analyses of census and housing market data, interviews with local experts, and focus groups with residents who contributed to inner city population growth in the study period. The findings determine that the strongest factor in the turnaround process was the tight rental market conditions prevailing throughout Winnipeg during the study period--a result of low private construction activity, economic uncertainty, high mortgage and interest rates, decreased inter-provincial out-migration, increased inter-provincial in-migration, and the ageing of the population in prime rental cohorts. Turnaround in inner city Winnipeg was accompanied by strong growth in preschool age children and young- and middle-aged adults ("babyboomers"), marginal socio-economic gains and increased impoverishment, and increases in the public housing stock. Three rationales were characterized for relocating to the inner city during the study period: relocating downtown because the downtown supported a lifestyle based on simplicity, convenience and access; relocating downtown because personal circumstances left no alternative; and relocating to an older inner city neighbourhood because of its sense of community, diversity, and character. The findings challenge the conventional notion that turnaround represents a renewed interest in inner cities as places of residence and is fuelled by upper class professionals attracted by new work and housing options.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".