Assessment Study of Export, Import Price Indexes and Their Foretell Trend in Case of Pakistan
Bibliographic record
Abstract
Purpose: This analysis examines the import and export price indexes and sudden changes in increasing curves in case of Pakistan.Methodology: In this case study the Spearman Rank correlation coefficient, denoted by !, is used for computation the association between both price indexes over the time period of sixteen quarters from 2012-15.Findings: The empirical results show that the two rankings i.e.Export Price and Import Price indexes have direct and significant relationship at the level of 0.05 level of significance (α) and Import and Export price indexes curves show a steady increase to upward on QoQ (Quarter on Quarter) basis.Recommendations: To strengthen economy government need to resolve energy issue through proactive measures and planning for attaining appropriate productivity by the industrial sector and increase exports goods to maintain balance of payment.The government should ensure the trade with neighboring countries and chalk out comprehensive plan for industrial estates to utilize potential youth edge and cheap labour to overcome unemployment and manufacturing cost.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".