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Record W3203585713

ViewPoint: Canada Should Establish an Equitable Growth Institute

2021· article· en· W3203585713 on OpenAlexvenueaboutno aff
Don Drummond

Bibliographic record

VenueInternational productivity monitor · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)Corporate governanceProductivityGovernment (linguistics)EconomicsSustainabilityComplementarity (molecular biology)Public economicsInclusive growthEconomic growthBusinessDevelopment economicsPolitical sciencePovertyFinance
DOInot available

Abstract

fetched live from OpenAlex

Canada faces serious economic challenges and needs strategic policy advice to succeed. Productivity growth must rise from the mediocre trend of recent decades. The spoils of growth should be more evenly distributed. As a carbon-intensive economy, the adjustment to net zero emissions will require fundamental change. The Government of Canada has benefited from advice from occasional advisory groups, but it has been decades since there has been a comprehensive, multi-year policy research effort. The time has come to establish an Equitable Growth Institute. It should align with the objectives of the Government but have sufficient independence to tackle tough issues. Provinces and territories must be involved as they hold many of the policy levers. In addition to having its own governance structure and researchers, it should bring together and where appropriate create networks of researchers. The Institute should delve into big questions of the day, including whether and how a Quality of Life framework can inform decision-making and whether there are tradeoffs or complementarity between economic growth and equity and sustainability objectives.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.042
GPT teacher head0.320
Teacher spread0.278 · 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.

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