Potential Global Competitiveness of Sri Lankan Virgin Coconut Oil Industry
Bibliographic record
Abstract
The study focuses on Sri Lankan virgin coconut oil industry because of it is one of the upcoming export products and also its position as one of the key player in the global market. Sri Lankan coconut industry is one of the major foreign exchange and employment generation source and element of the Sri Lankan nation. The study attempted to unearth the determinants of export competitiveness of virgin coconut oil industry in Sri Lanka by drawing attention on Porter’s theory of the competitive advantage of nations. The target population of the study consisted with individual firms which are engaging in virgin coconut oil export in Sri Lanka is two hundred and nineteen. The study used a likert scale to measure the chosen variables. Based on the Pearson Correlation analysis researcher can say that there is significance strong positive relationship between Availability of Raw materials, Quality of demand and Market share of export with the Export Competitiveness. According to regression analysis researcher can say that availability of Raw materials, Local market, Quality of demand and Market share of export has significance positive affect on Advantage of Export Competitiveness.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".