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Record W3010834169 · doi:10.1088/1748-9326/ab7f63

Shifting economic activity to services has limited potential to reduce global environmental impacts due to the household consumption of labour

2020· article· en· W3010834169 on OpenAlexafffund
Daniel Horen Greenford, Timothy Crownshaw, Corey Lesk, Konstantin Stadler, H. Damon Matthews

Bibliographic record

VenueEnvironmental Research Letters · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsMcGill UniversityConcordia University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsDamagesTertiary sector of the economyConsumption (sociology)EconomicsEconomic sectorDecoupling (probability)Economic impact analysisPrimary sector of the economyService (business)Natural resource economicsBusinessEconomyMicroeconomics

Abstract

fetched live from OpenAlex

Abstract The tertiary (or ‘service’) sector is commonly identified as a relatively clean part of the economy. Accordingly, sustainable development policy routinely invokes ‘tertiarization’—a shift from primary and secondary sectors to the tertiary sector—as a means of decoupling economic growth from environmental damages. However, this argument does not account for environmental impacts related to the household consumption of tertiary sector employees. Here we show using a novel analytical framework that when the household consumption of labour is treated as a necessary and endogenous input to production, the environmental impacts of all sectors converge. This shift in perspective also exacerbates existing disparities in the attribution of environmental impact from economic activity among developed and developing economies. Our findings suggest that decoupling of economic activity from environmental impacts is unlikely to be achieved by transitioning to a service-based economy alone, but rather, that reducing environmental damages from economic activity may require fundamental changes to the scale and composition of consumption across all economic sectors.

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
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
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.004

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 head0.042
GPT teacher head0.296
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations25
Published2020
Admission routes2
Has abstractyes

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