The Analysis of Impact of Changes in Canadian Trade Environment on Korean Trade after Joining CPTPP
Bibliographic record
Abstract
2021-03-14Korean trade due to Canada’s CPTPP accession and changes in the North American trade environment. Design/Methodology/Approach - From January 2015 to August 2020;the growth rate of Korea’s exports to Canada increased by 2.79% on average;and the standard deviation value reached 26.89%. Therefore;it was found that the standard deviation was relatively large;indicating that when Korea exported to Canada;the increase or decrease in Korea’s exports was severe due to tariffs or economic conditions. Accordingly;it is also necessary to examine how changes in the export environment such as Canadian policy or CPTPP membership can affect Korean exports to Canada from a long-term perspective. Findings - It is based on the results estimated from model of the ARIMA (1,1,0) over the period from 2015 to 2021 for the last four years;and it was found that Korea’s export growth rate to Canada will move around 10% in 2021. Research Implications - This can be inferred that the fluctuations in the growth rate of Korea’s exports to Canada may be greater when the impact of Canada’s CPTPP membership and the USMCA centered on the United States is visible. Therefore;in order to stabilize Korea’s export growth rate to Canada;a detailed analysis of North American markets such as Canada;Mexico and the United States should be additionally conducted.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".