Estudio comparado de las matrices tecnoeconómicas de Argentina y Canadá
Bibliographic record
Abstract
The objective of this work is to conduct a comparative study of the system oftechno-economic relations, specifically the incorporated R&D flows, that shapethe innovative process in Argentina and Canada. The analysis encompassesboth domestic and imported flows, utilizing Network Analysis to complementthe construction of technoeconomic indicators. The key findings indicate thatCanada has a higher degree of integration within its techno-economic systemcompared to Argentina. This finding is linked to Canada's greater absorptionof R&D within its productive system, with a lower reliance on imported components. These structural differences correspond to divergent sectoral profilesof their respective techno-economic structures. In light of these findings, it issuggested that the presence of a dynamic "Science Based" sector alone cannot compensate for the absence of "Specialized Providers" within the domesticcontext, which serves as a pivotal driver for disseminating technical progress.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".