MétaCan
Menu
Back to cohort
Record W3186320746 · doi:10.1016/j.oneear.2021.06.005

Meeting well-below 2°C target would increase energy sector jobs globally

2021· article· en· W3186320746 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOne Earth · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of British Columbia
FundersHorizon 2020Kirke-, Utdannings- og ForskningsdepartementetNorges ForskningsrådEuropean Commission
KeywordsFossil fuelWork (physics)Natural resource economicsClimate changeRenewable energyBaseline (sea)BusinessGreenhouse gasJob creationGlobal warmingEconomicsLabour economicsEngineeringPolitical scienceEcology

Abstract

fetched live from OpenAlex

To limit global warming to well-below 2°C (WB2C), fossil fuels must be replaced by low-carbon energy sources. Support for this transition is often dampened by the impact on fossil fuel jobs. Previous work shows that pro-climate polices could increase employment by 20 million net energy jobs, but these studies rely on Organisation for Economic Co-operation and Development (OECD) jobs data, assumptions about jobs in non-OECD countries, and a single baseline assumption. Here we combine a global dataset of job intensities across 11 energy technologies and five job categories in 50 countries with an integrated assessment model under three shared socioeconomic pathways. We estimate direct energy jobs under a WB2C scenario and current policy scenarios. We find that, by 2050, energy sector jobs would grow from today's 18 million to 26 million under a WB2C scenario compared with 21 million under the current policy scenario. Fossil fuel extraction jobs would rapidly decline, but losses will be compensated by gains in solar and wind jobs, particularly in the manufacturing sector (totaling 7.7 million in 2050).

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.052
GPT teacher head0.213
Teacher spread0.161 · 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