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Record W2292123233 · doi:10.1111/conl.12241

Private Landowners, Voluntary Conservation Programs, and Implementation of Conservation Friendly Land Management Practices

2016· article· en· W2292123233 on OpenAlex
James Farmer, Zhao Ma, Michael Drescher, Eric Knackmuhs, Stephanie Dickinson

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConservation Letters · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of Waterloo
FundersIndiana University
KeywordsStewardship (theology)BusinessLand tenureEnvironmental resource managementEnvironmental stewardshipEcosystem servicesEnvironmental planningTurnoverPrivate propertyLand useLand managementEcosystemGeographyEcologyEconomicsPolitical scienceAgriculture

Abstract

fetched live from OpenAlex

Abstract Private land conservation mechanisms are critical components employed by policy makers and conservation professionals to support the stewardship and protection of vital ecosystem services. While most research on voluntary conservation programs focuses on motives and barriers to participation, little is known about landowner activities and ecological status once property is enrolled in programs. Our mailed survey to landowners with property enrolled in the Indiana Classified Forest and Wildlands Program in U.S.A. revealed that (1) environmental motives, (2) residential motives like family life, and (3) having more land enrolled in the program were strong predictors of individuals who implemented conservation actions such as removal of invasive species and control of erosion. We also found that landowners witnessing environmental improvements on their land reported more conservation actions than those perceiving unchanged environmental conditions. A better understanding of landowner perceptions and conservation outcomes can help policy makers improve private land conservation programs.

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 score0.109
Threshold uncertainty score0.751

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 communication0.0000.001
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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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