Economische impact van het coalitieakkoord (2022-2025) op het zuivelcomplex
Bibliographic record
Abstract
In deze studie is verkend wat de potentiële economische impact van het coalitieakkoord 2022-2025 is op het zuivelcomplex.Er zijn drie scenario's richting 2030 doorgerekend: een basisscenario en twee scenario's waarin is gevarieerd met het budget dat is toegewezen aan de melkveehouderij en de snelheid waarin de maatregelen worden genomen.De scenario's zijn afgeleid van de aangekondigde maatregelen en budgetten in het coalitieakkoord en mede gebaseerd op een analyse van beleidsrapporten.In het basisscenario neemt het aantal melkkoeien af met 0,32 miljoen (-20,5%) en het melkvolume met 2,54 miljard kg (-18,2%) in de periode 2020-2030.De toegevoegde waarde van het zuivelcomplex daalt met 1,37 miljard euro.Op basis van de scenario's zijn de bepalende factoren, mogelijke knelpunten en neveneffecten van het coalitieakkoord bediscussieerd.This study explores the potential economic impact of the coalition agreement 2022-2025 on the Dutch dairy complex.Three scenarios towards 2030 have been analysed: a baseline scenario and two scenarios which varied in terms of the implementation speed of the policy measures and the public budget allocated to the dairy sector.The implemented scenarios were based on information derived from policy reports and budget information announced in the coalition agreement.In the baseline scenario, the herd size is projected to decreased by 0.32 million (-20.5%) and the milk volume by 2.54 million (-18.2%) in the period 2020-2030.The total value added of the dairy complex may decrease by 1.37 billion euros.Based on the assessment of the scenarios, key factors, potential bottlenecks and side effects of the coalition agreement are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".