The Steel Industry in Global Competition and Limited Capital: A Case Study of the Steel Industry in Bolivia
Bibliographic record
Abstract
This article has as its objective to present a study of the impact of tax costs of the investment destined to the expansion of a metallurgical plant in Bolivia, compared with the tax load that would occur if such the investment were made in other countries, specifically, the USA, Canada and Chile. The study has been developed within the context of recognition that certain events which provoke effects upon the level of competitiveness of companies are beyond their action range. Among such events, the tax load, an integral element of government macroeconomic policies, has been considered in this study. The multiple case study method was used to measure the tax cost of a planned investment, contemplating the effective legislation in each of the examined countries. Results of the study allow concluding that, among the four countries under analysis, Brazil presents the largest tax cost, significantly greater than the other countries, which offer fiscal incentives, including a negative tax load. Among the remaining three countries, the company competitiveness has been favoured according to the following order: by Chile, the USA and Canada.
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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 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".