Preparedness of Lao People’s Democratic Republic to Implement ASEAN Common Visa (ACV)
Bibliographic record
Abstract
The concept and practice of free migration has long existed, but the modern border pass and common visa have only been used since the establishment of the Schengen Agreement of the European Union in 1995. Since its establishment, the Schengen Visa has been an extraordinary example of the success of a borderless region and led to vibrant in growth and social development. ASEAN, as a new economic community that tries to set itself as a beneficiary of the lessons learned from the European Union, has been struggling in establishing its own common visa region. The reasons encompass economic, political, and social-cultural concerns. This study focuses specifically on the Lao PDR and it aims to assess the preparedness of the country if the region were to establish the common visa system. The study employs a qualitative approach and collects data via an interview questionnaire. Research data are collected from interviews of six high-ranking government officials. Using the theme generating and data coding approach in ATLAS, a qualitative data analysis program, this study found that the preparedness of the Lao PDR in implementing the ASEAN Common Visa (ACV) spans nine key factors: (1) geographical location, (2) visa policy, (3) immigration control, (4) quota of foreign workers in the private sector, (5) information and communications technology (ICT) in connectivity development, (6) electronic systems in the consular sector, (7) infrastructure, (8) population mobility, and (9) attitudes towards the ACV. After categorizing these factors based on economic, political, and social-cultural dimensions, it was found that population mobility is a common concern among the three dimensions. This suggests that the Lao PDR needs to focus on improvements in border management, synchronization of information and communication technology, infrastructure, and human resources development among the relevant sectors.
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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 | 0.004 | 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) | 0.003 | 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".