Bibliographic record
Abstract
Many large North American cities impose minimum parking space requirements on multifamily residential developments. Concern has arisen, however, that the high cost to provide these spaces raises housing prices in such complexes. Because no well-developed, formal market for parking spaces exists, this study attempted to estimate the implicit price of aboveground or underground parking spaces for condominiums located in central Edmonton, Alberta, Canada. Through the use of two real estate data sets, this study employed the hedonic method and tested for the presence of heteroskedasticity and for spatial autocorrelation when possible. Overall, the results suggested that consumers of bundled parking spaces received a large discount on such spaces. If the retail price were increased to include additional parking spaces, the higher price would not fully reflect the cost to provide such spaces. The affordability of housing might be adversely affected nonetheless. Developers, who are likely to be burdened by some of this indirect parking subsidy, may ultimately provide less housing to the market, which will lead to a higher market-clearing price. This study provided further empirical evidence to support the argument against the imposition of minimum parking space requirements. The requirements are likely to cause an oversupply of parking at multifamily residential developments.
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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 | 0.008 |
| 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 | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".