Who's Ready for Asean 2015? Firm Expectations and Preparations in the Philippines
Bibliographic record
Abstract
New-new trade theory makes predictions regarding the types of firms most likely to benefit from increases in economic openness. This paper exploits the launch of the ASEAN Economic Community in 2015 to test predictions regarding the types of firms that are optimistic about, and prepared for, increased regional integration. We introduce data from an original survey conducted just prior to the launch of the AEC of over 300 mostly multinational firms operating in the Philippines. We find that firms’ prior exposure to other economies in the region is a strong and positive predictor of both optimism and preparation. A firms' capabilities (i.e., size, profitability, and growth), on the other hand, predict preparation strongly and optimism only weakly. Of particular relevance to policy makers, we also find that firms’ primary policy demand on the Philippines government is for more information and communication, and that even highly capable firms make this demand. Our findings suggest that, despite outreach efforts by the Philippines government, a lack of information continues to impede firms’ abilities to seize the new opportunities associated with regional integration.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".