Technology-Intensive Suppliers as a Key Element for Structural Change in Latin America
Bibliographic record
Abstract
The current increase of commodity prices prompts the question regarding the extent to which the growth of primary industries is used as a basis of industrial development. Empirical evidence suggests the development of Technology-Intensive Suppliers (TIS) has played an important role in the industrialization process of the Nordic countries, Canada, and Australia. The development of local TIS may contribute to both reinforcing the industrial base and supporting structural change in developing countries. Therefore, it may provide a way to advance from natural resource dependence towards knowledge-based industrial activities. The TIS products are created under tailor-made concepts, giving solutions to their customers. TIS use knowledge and customer information to create innovation. These firms enhance value chains improving customer's competitive advantages (Dornberger & Torres, 2006). The relationship between the primary sector and its suppliers of technology can be seen as a backward linkage. Sectors with linkages of this kind use inputs from other industries (Hirschman, 1958). Hence, a fundamental goal of research in the context of developing countries is to understand the development of TIS and analysis of their improvement as a result of entrepreneurship intervention. This chapter covers the relevance of TIS firms in developing countries. TIS companies are frequently labeled as Micro-, Small-, and Medium-Sized Enterprises (MSMEs). In conclusion, the findings highlight the need to pay more attention to TIS organizations in developing economies. In Latin America, TIS firms contribute to the employment and diversification of the economic structure of the region through value-added products and services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".