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Record W4236152272 · doi:10.32920/ryerson.14648874

Creating incubator neighbourhood performing arts venues using growth financing tools

2021· preprint· en· W4236152272 on OpenAlexaffabout
David V. Godin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsToronto Metropolitan UniversityLangara CollegeSimon Fraser University
Fundersnot available
KeywordsIncubatorDowntownThe artsBusinessRentingNeighbourhood (mathematics)AmenityMarketingPlan (archaeology)Space (punctuation)Business planFinanceVisual artsGeographyEngineeringComputer scienceCivil engineering

Abstract

fetched live from OpenAlex

A recommendation that Vancouver City Council implement the Culture Plan’s commitment to address the persisting insufficiency of small rental performing arts venues by using Community Amenity Contributions (CACs) from the rezoning of properties to fund the creation of small, inexpensive ‘incubator’ neighbourhood performing arts venues, which are critical to the health and development of the performing arts community. The recommended development model is based on Havana Theatre; a small incubator performing arts venue located inside Havana Restaurant, which subsidizes the cost of operating the venue. In downtown, developers will build the venues and attached retail space using in-kind CACs. Outside of downtown, a ‘renovation-first’ approach will be taken by the City to buy existing buildings using accrued CACs and renovate them to create the venues and attached retail space. On the strength of experience and business plan, the City will select qualified bidders to operate the venues and attached businesses.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0680.010

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 head0.067
GPT teacher head0.239
Teacher spread0.172 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2021
Admission routes2
Has abstractyes

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