Regulation of the dairy processing industry by leading global exporters
Bibliographic record
Abstract
Introduction. In today’s globalised world, the dairy processing industry is crucial in ensuring food security and economic growth for many countries. Leading global exporters of dairy products face numerous challenges related to the regulation of this industry, including control over production values and prices, quality standards, product safety, etc. Studying the regulatory practices of the dairy processing industry in these countries provides valuable insights into which approaches contribute to the development of the sector and enhance its competitiveness in the global market. Purpose. The purpose of the paper is to conduct the analysis and comparison of dairy industry regulation strategies in leading exporting countries, to identify the threats and sustainability of their approaches. Methods. The research was carried out using the following methods: analysis and synthesis – to characterize the modern mainstream of theoretical intelligence in the field of regional security; comparative analysis – to compare the structures of regional security management in different parts of the world; deductions and inductions – to form a conceptual model of global governance; tabular and visual methods – for visual presentation of the material. Results. The article provides a retrospective review and comparison of dairy industry development programs in the European Union, the United States, Canada, and New Zealand over the past 50 years. New Zealand’s model is based on a market-oriented approach that integrates the dairy sector into the global economy, granting significant autonomy to market participants. However, despite its clearly neoliberal character, the state has played a crucial role in shaping the sector, with the leading dairy cooperative holding a near-monopoly status, indicative of a “neo-corporatist” model. In contrast, Canada’s approach involves substantial government intervention in dairy market regulation, reflecting a “neo-statist” model. The European Union and the United States employ a mixed regulatory framework incorporating elements of neoliberalism, neo-statism, and neo-corporatism. Discussion. The spread of neoliberal ideas and the implementation of its institutions have significantly impacted dairy industry regulation. Reforms have gradually dismantled the previous institutional hierarchy, compelling governments to adapt to global markets and competitive conditions. However, practice demonstrates that not all major dairy-producing countries have pursued deregulation. Instead, neoliberal principles have been adapted to national and regional contexts, allowing governments to maintain substantial interventions in the dairy sector of many leading nations. Additionally, following the COVID-19 pandemic and subsequent global geopolitical crises, there has been a resurgence of regulatory processes, accompanied by increasing regional tensions. These trends have been observed across various sectors, with the dairy industry also reflecting this historical shift. Prospects. In future scientific studies, it is advisable to more clearly define the problems and directions for improving the deregulation of the milk processing industry by the world’s leading exporters.
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 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 | 0.005 | 0.006 |
| 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 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".