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Collaborative Governance for Affordable Housing in Toronto and Melbourne

2020· article· en· W3089425550 on OpenAlex
Carolyn Whitzman, Katrina Raynor, Louise Frost

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Planning and Policy / Aménagement et politique au Canada · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of Ottawa
FundersU.S. Department of Health and Human Services
KeywordsAccountabilityGeneral partnershipAffordable housingCorporate governancePublic administrationPrivate sectorGovernment (linguistics)Collaborative governanceBusinessState (computer science)Local governmentPublic relationsFinanceEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Policy formation and implementation have largely shifted from a top-down government-led process, to a collaborative governance approach characterised by complex and opaque partnerships, weakly steered by the state. We use 36 interviews, undertaken in Toronto and Melbourne between 2015 and 2018, to assess procedural accountability in these two cities: the extent to which policy outputs developed through a partnership approach are fair, transparent, rational, and intentional. We find that both cities fail the basics of procedural accountability, and that there is little shared understanding amongst key partners – local and provincial/state policymakers, non-profit and private sector housing providers, and philanthropic and private sector finance providers – about the definition and missing quantum of affordable housing, let alone a sense of how to move forward.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.249
Teacher spread0.229 · 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