MétaCan
Menu
Back to cohort
Record W4408736509 · doi:10.1007/s11625-025-01664-0

Working at the crossroads of alternative currencies and degrowth: setting a research agenda

2025· article· en· W4408736509 on OpenAlexaff
Jérémy Bouchez, Marlei Pozzebon, Alexander Paulsson

Bibliographic record

VenueSustainability Science · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsDefence Research and Development Canada
FundersLunds UniversitetSvenska Forskningsrådet Formas
KeywordsDegrowthSustainable developmentLandscape ecologyPolitical scienceSustainabilityBiologyEcologyLaw

Abstract

fetched live from OpenAlex

Abstract In this review, we analyze the existing literature on the role of alternative currencies within degrowth. While degrowth emerged in the early 2000s alongside growing awareness of accelerating environmental crises and widening global inequalities, alternative currencies have a longer history. Alternative currencies have served as devices for communities seeking to become less dependent on the dominant economic system, but degrowth and technological advancements are potentially reshaping alternative currencies, both in what their purpose could be and in how they operate. When combined with degrowth, these currencies are often expected to foster greater resilience at the local level and slow down the pace of socio-ecological metabolism. Building on our review, we propose a research agenda that explores how policy proposals and concepts such as universal basic income, localization, and entropy can be understood in relation to alternative currencies. Our main contribution is to identify points of convergence and tension between alternative currencies and degrowth while proposing prospective research questions to guide future studies.

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)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0010.009
Scholarly communication0.0070.017
Open science0.0020.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.069
GPT teacher head0.342
Teacher spread0.274 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueSustainability ScienceSame topicHousing, Finance, and NeoliberalismFrench-language works237,207