MétaCan
Menu
Back to cohort
Record W2765265151

Mainstream and alternative sources of finance in Dutch agriculture

2017· article· en· W2765265151 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 · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsImpact
Fundersnot available
KeywordsLoanMainstreamAgricultureEquity (law)FinanceDebtBusinessEconomicsFinancial system
DOInot available

Abstract

fetched live from OpenAlex

In this paper mainstream and alternative sources of finance in Dutch agriculture are analysed. Dutch farmers make use of different sources of finance whereby bank loans continue to serve as the major source of debt financing. The average bank loan was approximately 740, 000 euro per farm in 2015 while equity amounted 1.8 million euro per farm. Traditional family loans amounted about 60, 000 euro per farm. Recent developments in, and examples of, alternative sources of finance indicate that the diversity will increase in the future, whereby various forms of financing will be used simultaneously. This can also be of interest for mainstream banks since their funding capacity is becoming more restricted as they are required to retain more capital to comply with the Basel Accords. The prospects for crowdfunding in agriculture are promising for projects relating to sales in niche markets. The relative low return on equity in agriculture indicates that private equity or venture capital is often not a viable option.

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 score0.789
Threshold uncertainty score0.804

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 communication0.0000.001
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 head0.014
GPT teacher head0.203
Teacher spread0.188 · 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