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Record W2608149323

International approaches to planning for employment lands

2014· article· en· W2608149323 on OpenAlexaboutno aff
Laura Schmahmann

Bibliographic record

VenuePlanning News · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsMetropolitan areaPlan (archaeology)JurisdictionEnvironmental planningBusinessRegional planningEnvironmental resource managementUrban planningPolitical scienceGeographyEngineeringEconomicsCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

As employment lands in the Sydney metropolitan area come under increasing pressure for conversion to residential uses, the need for a consistent and comprehensive policy for their protection becomes more urgent. New South Wales' existing planning policy framework is in a state of flux with a new Metropolitan Plan and Sub-regional Delivery Plans currently in preparation. A key challenge for these plans is ensuring that employment land needs at the LGA, Sub-regional and metropolitan levels are appropriately met while still allowing Councils to appropriately plan for lands within their jurisdiction. The approaches currently being used in the UK and Canada provide some examples of how these same challenges have been tackled elsewhere.

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: Other · Consensus signal: Other
Teacher disagreement score0.035
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0040.010
Scholarly communication0.0110.007
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0270.003

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 head0.129
GPT teacher head0.272
Teacher spread0.143 · 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
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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