ICT Institutional Framework in the Americas Region
Bibliographic record
Abstract
This paper builds on the federal indicator used by the ICT and development literature to answer the research question on what indicators better represent ICT institutional background in the Americas Region (Central America and the Caribbean Islands, North America and South America). Its main underpinnings are the concept of information revolution and the methodology put forward by the Telecommunications Law Indicators for Comparative Studies (TLICS) Model. Six sets of federal indicators on revenue, fiscal transfer, regulatory jurisdiction, adjudication, planning, and media content regulation are put together to compare ICT federal environment in the Americas Region as a groundwork for ICT comparative research. The empirical universe of the paper encompassed twenty-six countries from the Americas Region, that form a potpourri of twenty officially unitary countries – Belize, Bolivia, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Nicaragua, Panama, Paraguay, Peru, Suriname, Trinidad and Tobago and Uruguay – and six federal countries – Argentina, Brazil, Canada, Mexico, United States and Venezuela – that account for the most representative countries of the Caribbean Islands and all countries of Central, North, and South America apart from Guyana. The article is organized in three main parts. A brief description of the paper assumptions is performed in the first part. The second part applies TLICS variables to sets of the aforementioned states. The third part delves into the comparison of the states analyzed by means of categorizing the differences and commonalities revealed by more than one thousand variables collected in the legal and institutional framework of those countries and finally summarized in the ICT federal index (IFI) and ICT unitary index (IUI). We also tested the association between federalism as the outcome and each of the independent (explanatory) variables proposed by TLICS model by applying statistical tests of significance (Fisher exact test and relative risk). The only ICT variable significantly associated with a country being classified as a federal state is tax in the telecom, broadcast, broadband and e-commerce sectors. As a main outcome, based on data collected from the institutional background and legal frameworks of those countries, we found clusters of federal commonalities in federal and unitary countries of the region. With that, we proposed two indices that better represent federal and unitary institutional backgrounds: The ICT Federal Index (IFI); and the ICT Unitary Index (IUI). They provide a real picture of their institutional background for ICT and development comparative purposes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".