MétaCan
Menu
Back to cohort
Record W2504085123 · doi:10.1111/cjag.12111

Policy Experiments for the U.S. Intermountain West Native Seed Industry

2016· article· en· W2504085123 on OpenAlexvenueno aff
Betsy Mock, Kristiana Hansen, Roger Coupal, Dale J. Menkhaus

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
FundersWyoming Reclamation and Restoration CenterU.S. Bureau of Land Management
KeywordsEarningsLand reclamationProduction (economics)BusinessAgricultural economicsEconomicsEconomyForestryGeographyMicroeconomicsFinance

Abstract

fetched live from OpenAlex

The increasing frequency of fires and the focus on energy development in the western United States have expanded need for reclamation of disturbed lands. Government policy significantly influences demand for native seed and prioritizes use of native plants to improve reclamation success. However, existing native seed supplies are inadequate for current reclamation needs. The U.S. Bureau of Land Management (BLM) seeks to implement policies that will increase the quantities supplied. We conduct laboratory market experiments to analyze the effect of different policies BLM might implement on price, quantity traded, and earnings, especially in light of BLM's role in the market as largest buyer. Four treatments are examined, combining forward (production‐to‐demand) or spot (advance production) delivery and constant (seller unit earnings are constant and known) or variable demand (seller unit earnings randomly adjusted without notice) under big buyer influence (four sellers, two small buyers, one big buyer). A fifth competitive treatment (four sellers, four buyers) with forward contracting and constant demand provides a benchmark by which to gauge big buyer effects on market outcomes. Results provide evidence that adoption of forward contracting or reduction in BLM's demand variability would increase seller earnings and native seed production. L'augmentation de la fréquence des feux et l'attention particulière portée au développement énergétique dans l'Ouest américain créent un plus grand besoin pour la remise en état de terrains perturbés. Les politiques gouvernementales influencent significativement la demande pour les semences indigènes et priorisent l'utilisation de plantes indigènes pour accroître la réussite de remises en état. Par contre, les approvisionnements en semences indigènes ne répondent pas actuellement aux besoins de remise en état. Le Bureau of Land Management (BLM) des États‐Unis cherche à mettre en place des politiques qui augmenteront la disponibilité des semences. Nous menons des expériences de marché en laboratoire afin d'analyser les effets des diverses politiques qui pourraient être mises en œuvre par le BLM en matière de prix, de quantité négociée, et de revenus, tenant compte du rôle de BLM sur le marché à titre de principal acheteur. Quatre traitements sont étudiés, combinant la livraison à terme (production à la demande) ou à comptant (production anticipée), et la demande constante (les revenus à l'unité du fournisseur sont constants et connus) ou variable (les revenus à l'unité du fournisseur sont ajustés aléatoirement, sans préavis) sous l'influence de grands acheteurs (quatre fournisseurs, deux petits acheteurs et un grand acheteur).Un cinquième traitement compétitif (quatre fournisseurs, quatre acheteurs), avec contrats à terme et demande constante, fournit une référence contre laquelle il est possible d'évaluer l'effet du grand acheteur sur les résultats du marché. Les résultats fournissent des preuves selon lesquelles l'adoption de contrats à terme ou la réduction de la variabilité de la demande par BLM augmenterait les revenus des fournisseurs et la production des semences indigènes.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.198
Teacher spread0.178 · 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 designObservational
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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomieSame topicForest Management and PolicyFrench-language works237,207