Bakit Nagmahal ang Bigas Noong 2013? At Bakit Mahal pa rin? The Continuing Saga of Rice Self-Sufficiency in the Philippines
Bibliographic record
Abstract
The rice price spike experienced in the third quarter of 2013 alarmed the public. Speculations spread about the cause of the spike, the most popular of which was the hoarding by private traders. Rice cartels were also blamed for price manipulation. These cartels were perceived to connive with rice smugglers in an unholy alliance.It is easy to blame rice traders and smugglers for price manipulation, but it is another thing to produce evidence for this accusation. This Policy Note is the outcome of a study on the actual state of rice supply in the country. It looks into the rice price spike in 2013 by taking a different approach instead of subscribing to the notion of secret conspiracies. The alternative explanation taken by the study invokes nothing more than standard supply and demand. It proposes that the inadequacy of supply starting from mid-2013 can be attributed to the reduction in imports due to government policy. Such reduction was neither compensated for by a commensurate increase in domestic production nor by a timely release from the buffer stock.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".