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Record W2048047577 · doi:10.1017/s0889189300008754

Factors affecting the adoption of conservation tillage on clay soils in southwestern Ontario, Canada

2000· article· en· W2048047577 on OpenAlexaffabout
Johanna Wandel, John Smithers

Bibliographic record

VenueAmerican Journal of Alternative Agriculture · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsTillageAgricultureBusinessSoil conservationSample (material)AgroforestryAgricultural economicsEnvironmental resource managementGeographyEnvironmental planningNatural resource economicsEconomicsEcologyEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Despite significant progress in promoting the wider use of conservation tillage systems among farmers in Ontario, recent evidence suggests that adoption levels remain low overall, and especially low in those areas where agricultural soils are predominantly clay-based. Given the prominence of cash-crop agriculture in these regions, there is continuing interest in understanding the reasons for non-adoption in these areas, and in identifying strategies that would result in greater use of conservation tillage systems. This paper reports on an empirical analysis of conservation tillage adoption among a sample of 50 farmers in Lambton County, Ontario. The purpose of the research was to document and explain variations in the use of conservation tillage, and to assess prospects for increasing the adoption of this technology. A statistical analysis revealed that personal and attitudinal factors were largely unrelated to decisions concerning the use of conservation tillage. Instead, significant factors related to the scale of the farm operation as reflected in both farm size and sales, and in the nature of the farming system itself Subsequent analysis of farmers' stated motivations and perceived barriers suggests that inertia and uncertainty act as impediments to adoption. The findings point to the need for site-specific and farm system-specific information on the performance of this technology, and to the importance of benefits that are readily observable and communicable within local farming communities.

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 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 score0.279
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.237
Teacher spread0.213 · 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 teacher head, 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

Citations51
Published2000
Admission routes2
Has abstractyes

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