Future Earth and its prospects in South Asia
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
Future Earth’ was officially announced at the UN Conference on Sustainable Development (Rio+20) in 2012, and a permanent secretariat was set up in 2015. Future Earth is a global initiative aiming to create a sustainable and equitable world for all people. It uses a transdisciplinary research and system thinking approach in which basic and applied research are combined to produce knowledge that can be used to make decisions by practitioners and policymakers at all levels of governance. It works closely with the National and the International Science Academies and Society in advancing knowledge. Between 2021 and 2022, Future Earth underwent a transformation to become a more effective and inclusive organisation. At the moment, the day-to-day operations of Future Earth are facilitated by a well-distributed network of nine newly established Global Secretariat Hubs located in Africa, Canada, China, France, Japan, South Asia (hosted by the Indian Institute of Science), Sweden, Taipei, and the United States. Future Earth is a research program and the Secretariat aids in knowledge advancement through its various science communication products that are presented as policy briefs to head of states at various international forums. © 2022,Current Science. All rights reserved.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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