MétaCan
Menu
Back to cohort

Conservation of native woodland by farmers in Moree Plains Shire, New South Wales

2005· article· en· W2062048285 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAustralian Forestry · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsWoodlandShireAgroforestryGeographyVegetation (pathology)Quarter (Canadian coin)Introduced speciesGrasslandNative plantEnvironmental protectionEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Summary The New South Wales Government introduced the Native Vegetation Conservation Act 1998 to protect the native woodland and native grassland of the state. The amounts of native vegetation already conserved prior to the Act, the costs of continued conservation under the Act, and the farmers' wish to conserve or clear, are essential information to assist policy development in this area. To provide this kind of information, fifty-one farmers were interviewed in an important cropping region of the state, Moree Plains Shire. On average, 21.0% of the area of each farm in the sample was native woodland, and another 19.9% was native grassland. Over a quarter of the farms had at least 25% of their land in native woodland, and well over one-half had more than 10% in native woodland. The continued protection of this native vegetation under the Act imposes small costs on some landholders and high costs on others. Almost one-quarter of the farmers are losing only 5% or less of their potential income, but another quarter are losing at least one-half of their potential income. The farmers consider offsets to be an effective way for the state to promote conservation and compensate for some of their losses, and their wide range of suggestions for different kinds of offset is documented. The landholders who wish to clear more woodland are the poorer farmers who have the highest proportions of native woodland and grassland on their properties. The results are discussed in the context of current changes in the legislation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.555

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)0.0010.000

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 head0.094
GPT teacher head0.234
Teacher spread0.140 · 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