Exchange Rate and Country’s Export Competitiveness: An Empirical Discourse Analysis
Bibliographic record
Abstract
The objective of this study is to empirically analyze the discourse on correlation between exchange rate and country’s export competitiveness, which is one of the dominant discourses having been continuously and extensively reproduced in the Thai society by the authorities from academia, the public and private sectors. The study analyzes the time-series data of the exchange rate, overall exports, exports of agricultural products, and exports of industrial products by employing advanced statistical analysis, regression, and the Johansen Cointegration Test. Through regression, we find that exchange rate is negatively related to overall exports, exports of agricultural products and exports of industrial products. On the contrary, Johansen Cointegration Test does not demonstrate any long-term relationship between exchange rate and the three variables of export. Thus, the claim that the appreciation of domestic currency will negatively affect the country’s export competitiveness, whether in overall, agricultural products or industrial products, is not a defect in good faith but another example of the dominance of oriented discourse, which gives way for the elite to take advantage as a camouflage in the form of knowledge and truth, while others in the society never suspect nor argue about it.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".