Predicting farmer uptake of new agricultural practices: A tool for research, extension and policy
Includes insightful questions such as:
To what extent is the adoption of the practice able to be reversed?
To what extent is the use of the practice likely to affect the profitability of the farm business in the years that it is used?
How easily can the practice (or significant components of it) be trialed on a limited basis before a decision is made to adopt it on a larger scale?
The use of process-based models for agricultural GHG projects generally entails evaluation of model performance (termed “validation” in many protocols) using existing datasets deemed representative of project activities and context…
The datasets available for such validation efforts are highly limited…
22 people have published more than 200 papers in 2024 (so far, we still have another six months to go) …
Is it possible for anybody to contribute in a meaningful way (at least to warrant being at author) when they are publishing a paper every day?
Data Management in Large-Scale Education Research
Center for Open Science (cos.io)
One initiative is SMART: Scaling Machine Assessments of Research Trustworthiness. Something to think about, that AI tools may one day assess out research as it might be less susceptible to being distracted by jargon and incoherent writing.
xkcd: Bad Map Projection: Exterior Kansas
This is so bad, but too funny to look away from.
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