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Record W1768065509

Rethinking Governance: Supporting Healthy Development Through Systems-Level Collaboration in Canada’s Provincial North

2015· article· en· W1768065509 on OpenAlexaffabout
Rebecca Schiff

Bibliographic record

VenueNorthern review · 2015
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsLakehead University
Fundersnot available
KeywordsCorporate governanceContext (archaeology)Government (linguistics)Food systemsBusinessService delivery frameworkEconomic growthCollaborative governanceResource (disambiguation)Service (business)Environmental resource managementEnvironmental planningFood securityMarketingGeographyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Communities across Canada’s Provincial North experience significant barriers to providing adequate food and housing. The ability to deliver these essential services is further complicated by rapid economic growth and industrial development. Although significant in terms of facilitating development, critical issues associated with food and housing often fall through the gaps of government policy and decision making. Happy Valley-Goose Bay (HVGB) is a remote service-centre community in Labrador experiencing both rapid resource and economic development and the associated pressures on delivery of essential services such as food and housing. In response to these pressures, systems-level collaborative approaches to food and housing issues were developed in an attempt to reconcile policy gaps and address growing needs. This article investigates the significance of food and housing issues in the growth of Canada’s northern communities. Within that context, the gaps in governance of food and housing issues are also examined. The experience of HVGB illustrates the nature of food and housing stress in these communities and how systems-level food and housing collaboratives can lead to innovative and cost-effective solutions to addressing and supporting demand for growth.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.119
GPT teacher head0.392
Teacher spread0.273 · 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 teacher head, not a consensus.

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

Citations1
Published2015
Admission routes2
Has abstractyes

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