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Record W2101539577

Farmers’ preference for soil and water conservation practices in central highlands of Ethiopia.

2013· article· en· W2101539577 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.

fundA Canadian funder is recorded on the work.
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

VenueTSpace · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
FundersEthiopian Institute of Agricultural ResearchInternational Development Research Centre
KeywordsSoil conservationGeographyWatershedSoil waterAgroforestryLand tenureMathematicsAgricultural economicsEnvironmental scienceAgricultural scienceAgricultureEconomicsSoil scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Land degradation is a major socio-economic and environmental concern in the Ethiopian highlands where the phenomenon has rendered vast areas of fertile land unproductive. To reverse this trend, the adoption of soil and water conservation (SWC) practices is crucial. However, failure by research and development organisations to take into consideration farmers preference for SWC practices have resulted into low adoption of these technologies. This paper presents the findings of a study that evaluated farmers ’ preferences of SWC practices, including the economic perspective; as a basis for enhancing adoption of the technologies in the central highlands of Ethiopia. Four soil and water conservation (SWC) practices; (i) soil bunds alone (SB), (ii) soil bunds with vetiver grass (SB+Vg), (iii) soil bunds with Susbania susban (SB+Ss) (iv) and soil bunds with elephant grass (SB+Eg), were evaluated in the Borodo Watershed in the central highlands of Ethiopia. These are the only SWC measures introduced and implemented in Borodo watershed. Data on these SWC practices were collected from farmers using focus group discussion. A multi-criteria analysis (MCA) approach was used to analyses the data. The criteria were weighted using pair-wise ranking and SWC practices were scored with a scale of 1(not good) to 5 (best) based on each criterion. The overall weighted scores were obtained using the Simple Additive Weighting Model. Farmers assigned highest relative weights to criteria related to economic criteria (0.58) than technical

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.792

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)0.0000.000

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 head0.096
GPT teacher head0.310
Teacher spread0.214 · 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