Role of Social Media in Socioeconomic Development: Case of Facebook
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
To study the role of Information and Communication Technology (ICT) on countries’ socioeconomic development, the paper investigates the case of Facebook penetration on improving their standing as measured via GNI per capita PPP (Gross National Income per capita based on purchasing power parity). We use four macro factors categories (political, economic, demographic, and technological) in addition to Facebook penetration per capita in order to measure the potential influence of various factors on the socioeconomic level of countries. While the analyses of ICT effect on development has been the focus of many papers in the past, the specific analysis of social media is scarce. Compared to previous studies investigating social media role, we use a large dataset covering all classes of countries and examine holistically many types of determinants using different models. In addition, we distinguish our paper using the economic classification of countries according to the World Bank. Our study indicates that Facebook penetration has a significant positive role on the socioeconomic level of countries, but such role varies depending on the countries’ classification level. Besides, there is a decreasing marginal effect showing the importance for policy makers to assess the complex dynamic behind the characteristic of each country.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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