Bibliographic record
Abstract
The study analyzes the impact of the MICE Industries in terms of employment effect and economic contribution to the national economy(GDP) among US, Canada, Mexico, and UK. The results of this study are as follows: (1) US had the highest employment effect with 5.31 million people. UK, Mexico, and Canada had also high employment effect of 1.02 million, 783 thousand, and 341 thousand. (2) The total GDP contribution was the highest in the United States with $ 393.8 billion. It reached ￡ 35.9 billion in the UK, CAD$ 27.5 billion in Canada and US$ 25.1 billion in Mexico. (3) UK ranked highest with 3.83 percent of GDP contributions. US, Mexico and Canada also saw 2.4percent, 2.41 percent and 1.51 percent respectively, contributing to the economic contribution of the MICE Industries. It is also necessary for our nation to adopt internationally standardized methodology to analyse the employment effects and economic contribution of the MICE Industries. Also, it would be important to understand the relative position of our industry, comparing the results to other countries.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".