The Future of Knowledge Sharing in a Digital Age: Exploring Impacts and Policy Implications for Development
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
We live in a Digital Age that gives us instant access to information at greater and greater volumes. The rapid growth of digital content and tools is already changing how we create, consume and distribute knowledge. Even though globally participation in the Digital Age remains uneven, more and more people are accessing and contributing digital content every day. Over the next 15 years, developing countries are likely to experience sweeping changes in how states and societies engage with knowledge. These changes hold the potential to improve people’s lives by making information more available, increasing avenues for political and economic engagement, and making government more transparent and responsive. But they also carry dangers of a growing knowledge divide influenced by technology access, threats to privacy, and the potential loss of diversity of knowledge. Our research sets out with a 15-year horizon to look at the possible ways in which digital technologies might contribute to or damage development agendas, and how development practitioners and policymakers might best respond.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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