Regional Information for Society within the World Climate Research Programme
Bibliographic record
Abstract
The World Climate Research Programme (WCRP) has created a new core project: Regional Information for Society (RIfS), which has begun to plan its inaugural activities. Recognizing a gap between core disciplinary projects of WCRP and societal impact, RIfS seeks to foster community exchange around the practices of creating and utilizing climate information. The members of the Scientific Steering Group and International Project Office see this as a collaborative process with stakeholders from various sectors of society. Rather than reproducing more climate services, we are focused on identifying best-practices, building worldwide capacity and equity, and contributing to existing projects at the regional scale, particularly in regions where there are limited resources for such services. This RIfS presentation will focus on the identification of best-practices, particularly in the assessment of climate information. Currently there is no systematic, consistent, or accepted approach to assessing which climate information is robust and actionable, at regional or global scales. This recognizes the multiplicity of non-congruent data and information sources that may be used, the choice of which depends often on subjective selections that can lead to different decision outcomes and the commensurate consequences. At the same time, the volumes of data and demand for information are only growing, and new organizations are emerging offering products to decision-makers with varying levels of transparency about methods. Decisions are being made that affect the global distribution of resources, for example in finance and the insurance sectors. No professional organization has so far managed to establish widely accepted standards and guidelines for what constitutes robust information appropriate for various types of decision-making. This is the central challenge of the moment for the community of climate researchers interested in societal applications. RIfS will begin a process of consensus-building with an expert meeting on robustness of climate information just after the EGU meeting this year, to be followed by additional opportunities to come together around these questions.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.021 | 0.011 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.107 | 0.065 |
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".