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Record W4400288285 · doi:10.5194/epsc2024-1054

IPSL Climactions and the bottom-up ecological transformation of a climate and planetary science research institute (2016-2024)

2024· preprint· en· W4400288285 on OpenAlexaboutno aff
Léa Bonnefoy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsTop-down and bottom-up designTransformation (genetics)Environmental scienceClimate changeClimatologyOceanographyEcologyGeographyEngineeringGeologyBiology

Abstract

fetched live from OpenAlex

For several decades now, research communities working on the climate, its changes, including current global warming, and its consequences have been recommending drastic reductions in human-made greenhouse gas emissions and, more generally, in the ecological footprint of human activities. This implies the implementation over the next 10 to 20 years of profound and rapid systemic transformations. The latest IPCC reports show that such transformations are only possible if they involve all parts/sectors of society. Given the existence of a range of ecological constraints and the foreseeable limits to scientific and technical advances, the transformations to be implemented must also include a strong component of sufficiency ("avoidance”).The IPSL (Institut Pierre-Simon Laplace) is a federation of academic research laboratories in the region of Paris, France, incl. CEREA, GEOPS, LATMOS, LISA, LMD, LOCEAN, LSCE, and METIS, which address all climate-relevant components of the Earth System, but also study other planets of the solar system. Since 2016, IPSL scientists and support staff have been working together along these lines to transform the institute's professional practices. This engagement is generally seen as : (i) a necessity: to initiate a transition in its research practices that will bring its professional behavior in line with the message of climate urgency that it has been diffusing for over 30 years; (ii) an opportunity: to accelerate the transition at a societal level by opening up new channels of exchange with society, encouraging collective action by example, and reinforcing the credibility of its warning message; (iii) a safeguard: collective bottom-up thinking at laboratory level to ensure that this transition takes place with maximum respect for our research practices and our well-being at work, and is not imposed by potentially inappropriate top-down measures.Achievements include (i) the development of methodologies for calculating the carbon footprint generated by staff activities and professional practices, (ii) concrete contributions to the reduction of the environmental footprint of professional travels, digital and high performance computing activities, purchases and finally observation of the earth. So far, the carbon footprint reduction efforts do not affect research methods, which constitute the core of the institute’s activity. However, the carbon emissions of the institute cannot be significantly reduced without a profound change in the way climate and planetary research are conducted, including data collection techniques (field campaigns, space missions, polar stations, etc), supercomputing, or laboratory instruments. The central question we are asking is: how do we continue to do new and interesting planetary science today while minimizing carbon emissions and other environmental impacts? A collective discussion around this thematic has been initiated in the IPSL; we will present here our approach, methodologies, achievements, and reflections at this stage, with the hope to stimulate exchange with other ongoing or emerging initiatives in other parts of the world. Figure 1: Carbon footprint of the IPSL for 2019, with the contribution of each category given in CO2 equivalent tons.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0140.006
Open science0.0030.013
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.1060.064

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.

Opus teacher head0.025
GPT teacher head0.288
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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