A Century of Saudi-Qatari Food Insecurity: Paradigmatic Shifts in the Geopolitics, Economics and Sustainability of Gulf States Animal Agriculture
Bibliographic record
Abstract
In their quest for food security, the drylands of the Gulf Cooperation Council states have experienced more radical transformation over the past half century than over the previous millennium. This paper explores modern revolutions in the animal agriculture of Gulf Arab States, focusing on Saudi Arabia and Qatar as case studies. We identify three main paradigmatic shifts in the history of animal agriculture in Saudi Arabia, and four in the case of Qatar. From the 1950s to the 1970s, the Gulf monarchies increasingly settled their tribes into sprawling cities, started to massively import food and put an end to nomadism as a form of livelihood. By the 1960s and 1970s, unprecedented oil revenues and new geopolitical risks to their food supplies led the Gulf states to embark on a wave of state-supported agricultural modernization and food self-sufficiency programs, with generous land allocation, various subsidies and interest-free loans, inter alia. After several decades however, this vision of ‘turning the desert green’ proved both environmentally and economically unsustainable, especially after the 2008 and 2014 falls in oil prices. In more recent years, there have been growing counter-tides of subsidy cuts, marketization, and increased regulation. In Qatar however, this trend came to a halt on June 5th, 2017, when a major diplomatic crisis erupted among Gulf Arab countries, leading to a dramatic land and air blockade of Qatar's food supplies. Once again, state intervention, subsidies, and mass production methods have been deployed to boost national food security, relegating economic rationality and sustainability to a hypothetical future.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".