International Round Table: Financing Climate Action at City Level. CAST Report, October 2024.
Bibliographic record
Abstract
An online International Round Table on Financing Climate Action at City Level took place on November 15th, 2023. Participants were from city and regional governments in Canada, France, Germany, Italy, Norway, the USA and the UK (see end for details). The event enabled the exploration of financial issues associated with city-level climate action. It was a follow-up to an earlier international round table on accelerating climate action at city level, where finance was identified as a topic of particular interest. The follow-up round table was co-hosted by the Centre for Climate Change and Social Transformations (CAST), The Tyndall Centre for Climate Change Research and the Greater Manchester Combined Authority (GMCA). Presentations were given by officials from Bristol City Leap, as well as Oslo and Greater Manchester authorities, but the majority of the event was allocated to discussion. All participants were officials tasked with implementing ambitious climate change mitigation plans, or their colleagues working in business or finance. The purpose of the round table was to provide a space for these people to share their experiences and learn from each other. Participants were encouraged to talk about challenges as well as successes. This report summarises the points that emerged from the discussions. It is not a list of simple solutions, nor does it represent the authors’ or round table participants’ final position on ‘how to finance climate action’. Instead, it is an indication of the financial issues that people working on city-level climate action are facing and the approaches they are taking to make progress.
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.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.186 | 0.086 |
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".