City planning and the political and fiscal repercussions of high unemployment
Bibliographic record
Abstract
The environment of city planning practice includes increasing unemployment rates in the communities practitioners serve. There should be effects of this; however, there is little discussion in the literature of the relationship between high unemployment and planning. This thesis is an exploratory study of that relationship. It examines the effects of high unemployment on city planning as mediated by the political and fiscal environments. Three levels of planning are considered: strategic, normative, and operational planning. The subjective quality of the workplace is also considered. A preliminary review of the literatures on unemployment, on political participation and its economic antecedents, on planning, and on municipal fiscal stress, was followed by interviews with twenty-two planners, councillors, and administrators of nongovernmental services for the unemployed. The thesis describes the relationship between unemployment and political participation. (Canadian data on magnetic tape which can be used in quantitative work in this area are listed in the Appendix.) The implications of that relationship are then developed for city planning. The effects on planning of unemployment-related municipal fiscal pressure are also explored. A number of hypotheses are generated which take into account contextual effects. These are incorporated into four future scenarios which make different assumptions about the ability of left- and right-of-center governments to reduce the unemployment rate. The thesis concludes with directions for future research and some general issues.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".