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Record W6884640864 · doi:10.11575/prism/30016

The Future of Calgary's Community Parks

2015· other· en· W6884640864 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAffordable housingLegislatureLegislationVariety (cybernetics)Land usePublic landPoliticsUrban planning

Abstract

fetched live from OpenAlex

In Alberta, municipal policy regarding the preservation of urban park space has been evolving since legislative changes were made in 2010 to enable municipalities to use surplus school reserve sites for a range of purposes in addition to green space. Many competing demands for these sites have been put forth by a variety of proponents, including citizens and community associations, school boards, the development industry, affordable housing providers and advocates, and municipalities. This capstone project examines the politics that underlie the current public policy debates on these competing uses of municipal park space in Alberta, in particular, the reuse of vacant school reserve sites for affordable housing. The desire to build affordable housing or other community services on Municipal and School Reserve (MSR) lands has arisen as a result of two economic factors: 1) Alberta’s resource-based economy creates a short-run, cyclical volatility in housing demand and pricing; 2) this is exacerbated by the long-term goal of reducing urban sprawl, which puts upward pressure on land costs by restricting the supply of suburban land available for new housing. In Alberta, these factors came together when the “superheated economy” of 2006 and 2007 strained housing supply across the province, doubling house prices in three years, and leaving many with inadequate shelter. One solution that has been embraced by municipal and provincial leaders in both Calgary and Edmonton is the use of vacant school reserve sites for affordable housing. In 2010, legislation was amended to allow vacant school reserve sites to be used for affordable housing or other community services, instead of being used for parks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.115
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.005
Scholarly communication0.0110.002
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0250.001

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.

Opus teacher head0.012
GPT teacher head0.208
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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