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Record W3097712530

Towards sustainable and circular farming in the Netherlands: Lessons from the socio-economic perspective

2020· article· en· W3097712530 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.

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

Bibliographic record

VenueSocio-Environmental Systems Modeling · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsImpact
Fundersnot available
KeywordsSustainabilityIncentiveAgricultureBusinessProduction (economics)Circular economyScale (ratio)Natural resource economicsSustainable developmentPrivate sectorEnvironmental economicsEnvironmental resource managementEconomicsEconomic growthMarket economyGeography
DOInot available

Abstract

fetched live from OpenAlex

The dutch dairy sector has shown a strong development in the last decades, resulting in fewer but larger and more specialised farms. Larger farms and more intensive ways of production have raised concerns about environmental impacts. This paper shows that there is a clear economic incentive to increase the scale of production. Larger farms tend to show better economic results in terms of lower cost prices and higher incomes. The environmental results are more diverse and depend on the chosen indicators. Larger farms are able to include environmental objectives in their farm management when there are clear incentives to do so. These incentives can be provided by policies, but also by private sector initiatives. Several sustainability initiatives have been developed to monitor and improve the sustainability performance of farms. Our current way of agricultural production is faced with several sustainability challenges. Circular food systems are expected to contribute to the solution of these challenges. In the Netherlands, policy measures and sector initiatives are developed to increase sustainability and to implement and experiment with the concept of Circular Agriculture. This concept is deliberately broadly defined. However, to guide development towards more sustainable production systems, it requires objective parameters and goals at different levels of scale. This would allow all stakeholders to develop solutions in their own circumstances and objectively evaluate progress. One of the bottlenecks of the transition towards more circular food systems is the search for new business models for farmers. Some frontrunners are currently developing new circular farming businesses. These innovative (social) entrepreneurs are experimenting with new business models that contribute to the realisation of circular agriculture. This paper describes methods that have been developed to assist farmers but also regional governments in the transition to a more sustainable agriculture and the development of new business models. Developing new business models together with frontrunners is just a first step. Questions like ’How to broaden these initiatives to sector level?’, ‘How to provide effective incentives?’, ‘How to incorporate external effects in prices?’ and ‘What are the costs of farm investments or practices to improve sustainability?’ and ‘Who should pay for a more circular agriculture?’ are still very much unanswered.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.802

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 studies0.0010.000
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 head0.020
GPT teacher head0.206
Teacher spread0.186 · 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