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Record W4362677196 · doi:10.1080/14702541.2023.2194285

Loss and Damage from climate change: legacies from Glasgow and Sharm el-Sheikh

2023· article· en· W4362677196 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScottish Geographical Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
FundersInternational Development Research CentreWellcome Trust
KeywordsDamagesClimate changeLoss and damagePolitical scienceGeographyLawForensic engineeringGeologyEngineering

Abstract

fetched live from OpenAlex

Conferences of the UN climate change convention have legacies both in formal outcomes and treaties and in raising the profile of emerging climate dilemmas. The joint legacies of COP26 in Glasgow and COP27 in Sharm el-Sheikh have been in elevating the profile and formalising the potential for solidaristic action on ‘Loss and Damage’ from climate change. This article reviews the documented outcomes on Loss and Damage from the two events to analyse the significance and constraints of this element of the overall climate change regime. Loss and Damage is likely to be constrained as a global collective action by the capacity to identify and measure losses and damages and by the ability of the climate change regime to deliver on meaningful resource transfers. Yet the formalisation of elements of climate justice through Loss and Damage is a real and lasting legacy of these COP events.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.078
GPT teacher head0.325
Teacher spread0.247 · 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