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Record W2886717866

The possible implementation of the income stabilisation tool in Wallonia

2018· article· en· W2886717866 on OpenAlexaboutno aff
Philippe Burny

Bibliographic record

VenueOpen Repository and Bibliography (University of Liège) · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Analysis and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness
DOInot available

Abstract

fetched live from OpenAlex

After several reforms of the Common Agricultural Policy and the disappearance of intervention prices and production quotas, price volatility is the rule on agricultural markets and, as a consequence, farm income is more and more unstable and unpredictable. In such conditions, risk management becomes an important tool within the CAP (regulation (EU) n° 1305/2013, regulation (EU) 2017/2393). In such a context, the Walloon administration dealing with agriculture ordered a preliminary study in order to examine the possible implementation of the income stabilization tool (IST) in the region. The paper deals with examples from Canada, the United States, Spain and Italy and with scenarios about Wallonia. Two hypotheses were tested : an income loss of 20% and 30% compared to the mean income of the previous period of three years. The used data come from the FADN network. The tested period covers the years from 2010 to 2016 included, so that the implementation of the IST is examined for four years, from 2013 to 2016. The calculations are made on the total FADN sample (more than 400 farms) on one hand, and on four specialized farm groups : bovine meat, milk, general crops, crops and cattle, on the other hand. The results show that the IST would not have been implemented when the total sample is considered. When specialized farm groups are considered, the IST would have been implemented only for the threshold of 20% of income loss, once for the dairy, once for the general crops and once for the crops and cattle specialized farm groups. The first condition being fulfilled, the calcultations are made for each individual farm, and Financial compensations are granted to farms which have registered an income loss of at leat 20%. Then the mean compensation for the specialized farm groups is extrapolated to the regional Walloon level. The compensation is fixed at 70% of the loss and the public support to this compensation is fixed at 70%. The public subsidies must be co-financed at least by 25% from the EU budget. Finally, it appears that the potential cost of the IST is affordable, but the participation of the farmers in this mutual fund is uncertain, making the success of the IST still doubtful.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.231
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2018
Admission routes1
Has abstractyes

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