Is There a Global Digital Divide for Digital Wireless Phone Technologies?
Bibliographic record
Abstract
This research examines digital wireless phone adoption among nations and regions that will help to provide a picture of the current global "digital divide." The data are drawn from 43 countries. We present a new theoretical perspective for IS research: a regional contagion theory of technology diffusion. We examine the efficacy of the new theory using empirical regularities analysis, and a vector autoregression and variance decomposition approach to establish information about the strength of the regional contagion links between countries in digital wireless phone diffusion. We found that faster growth of digital wireless phones occurs when a country has: a more well-developed telecommunications infrastructure, more competition in the wireless market, lower wireless network access costs, and fewer wireless technology standards. We also obtained a reading on cross-national influence of wireless diffusion. The countries we studied fell into three regional contagion groups: high, medium and low. The Asia Pacific countries revealed a pattern of homogeneously high regional contagion links, while Western European countries were divided across the three groups. Our findings are supported by a descriptive analysis of diffusion patterns and mini-case assessments.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.012 |
| 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".