The Impacts of Socio-Economic and Cultural Factors on the Network Readiness of Nations: A Focus on the Regions of Africa
Bibliographic record
Abstract
The Network Readiness Index (NRI) was developed to measure the propensity for countries (and regions) to exploit information and communications technology (ICT) for development and growth. Much has been written about the influences of economic and non-economic factors on ICT diffusion in developed societies. Studies examining the impact of relevant factors on Africa’s regions’ capabilities to exploit ICT for development are scarce. Moreover, where such studies exist, it is not uncommon for the African continent to be taken as a monolith. This paper argues that the NRI scores for countries across the geographical regions of Africa vary by socio-economic and cultural factors. Hypotheses were developed to test this assertion. The data analysis showed that there are differences across Africa’s regions with respect to the NRI. The data also found relationships between some socio-economic factors, cross-cultural dimensions, and the NRI. The study’s implications for research and policy making are succinctly discussed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".