Toekomstperspectief agrosector Flevoland
Bibliographic record
Abstract
De sociaaleconomische toekomst van de provincie Flevoland hangt deels samen met de perspectieven van het agrocluster, het totaal van land-en tuinbouwbedrijven, visserij, voedings-en genotmiddelenindustrie en de aan deze sectoren toeleverende bedrijven.In dit rapport is het belang van dit cluster voor Flevoland in kaart gebracht, met een accent op de primaire sectoren, de land-en tuinbouwbedrijven.De huidige situatie van deze bedrijven is in beeld gebracht evenals de ontwikkelingen in de afgelopen tien jaar en de perspectieven voor de komende tien jaar.Daarbij is ook aandacht besteed aan de leefbaarheid van het platteland en de invloed van de agrosector daarop.The socio-economic future of the Dutch province of Flevoland is partly linked to the perspectives of the agrocluster, the combination of agri-and horticultural firms, fishery, food and luxury industry and the firms that supply these sectors.In this report, the importance of this cluster for Flevoland is described, with a focus on the primary sectors, the agri-and horticultural firms.The current situation of these firms is presented, including the developments in the recent decade and the perspectives for the next decade.Attention is also paid to the quality of life in the countryside and the influence of the agro sector on this aspect.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.006 |
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".