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Record W7043502890

Strategy For Structures: Lessons In Community & Regional Economic Development

2007· article· en· W7043502890 on OpenAlexaboutno aff

Bibliographic record

VenueAUSpace (Athabasca University) · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsDevolution (biology)Local economic developmentPower (physics)Convergence (economics)Representation (politics)Distribution (mathematics)Local governmentReading (process)
DOInot available

Abstract

fetched live from OpenAlex

The current distribution of power between local, regional, and national governments often runs contrary to common sense as well as economic reality. There is no cut-and-dried solution. But research into recent experience in the North Atlantic Rim clarifies the capacity that must be cultivated at the local level so that a sensible and effective devolution of authority can proceed. Greenwood’s simple but effective representation of how power, authority, and resources are distributed between the federal, provincial and local levels in Canada represents a thoughtful and powerful judgment of how the system works against the harnessing of local knowledge and capacity so crucial to development in the modern economy. Comparing the results of the research this article reports with others in this section (Lewis, 1994; O'Regan and Conway, 1994; Lewis, 2000; Greenwood, 2000) reveals a fascinating convergence of conclusions as well as serving to enrich the texture and nuanced understanding to be gleaned from a careful reading of this cluster of contributors.

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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.017
Scholarly communication0.0120.010
Open science0.0020.004
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0170.002

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 head0.055
GPT teacher head0.260
Teacher spread0.205 · 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
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
Published2007
Admission routes1
Has abstractyes

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