The impact of <scp>ICT</scp> development on economic resilience during the <scp>COVID</scp>‐19 pandemic: A country level analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This research explores the relationship between information and communications technology (ICT) development and its impact on a country's economy during the COVID‐19 pandemic. This study has two primary objectives: (1) to understand how ICT development influences a country's economic resilience during a crisis, and (2) to examine the interrelationships between various country‐level ICT development measures. We use multi‐year, country‐level data made available by the United Nations, the World Bank, and World Health Organization to empirically examine our research model. Partial least squares path analysis is the primary research methodology employed in this study. Our results suggest that ICT development has a positive impact on economic resilience in the face of the COVID‐19 pandemic. In addition, our results specify the interrelationships between individual ICT development measures and economic resilience. This research contributes to the extant body of knowledge on the impact of country‐level ICT development on economy by empirically validating a research model that explores the relationships between the various measures of ICT development and economic resilience of countries during the COVID‐19 pandemic.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it