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Enregistrement W4401809953 · doi:10.55016/ojs/sppp.v6i1.42444

The “Green Jobs” Fantasy: Why the Economic and Environmental Reality Can Never Live Up to the Political Promise

2013· article· en· W4401809953 sur OpenAlexaffabout
Jennifer Winter, Michal C. Moore

Notice bibliographique

RevueThe School of Public Policy Publications · 2013
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueEconomic Theory and Institutions
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésFantasyPoliticsEnvironmental ethicsPolitical scienceArtPhilosophyLiteratureLaw

Résumé

récupéré en direct d'OpenAlex

Agriculture is one of the least “green” — that is, the least environmentally friendly — sectors in Canada, based on its energy-use intensity and greenhouse gas emissions intensity. But agriculture is also the “greenest” sector in Canada, according to one measure that calculates the proportion of “green employment” in various industries. Welcome to the world of “green jobs,” where vague definitions often give energy-intensive, carbon-heavy industries a “green” stamp of approval. Examples include companies making solar panels, but using large volumes of energy to do so or where an accountant preparing financial returns is counted as a “green” worker at one office, but turns instantly “dirty” should he cross the street to do the same accounting work at another office. It is also a world where inefficient power generation is considered positive, if it means employing more “green workers” per unit of power output, regardless of any negative effects that may have on the economy. The concept of “green jobs” has become immensely popular among policy planners looking to address the problem of global warming, yet are aware of the economic costs of anti-carbon measures. The promise that western economies can reduce carbon emissions while creating thousands, if not millions, of “green jobs” — which will more than compensate for the job losses that will occur in sectors reliant on fossil fuels — has been especially embraced by politicians, relieved to find a pro-climate policy that also doubles as a pro-economic policy. Unfortunately, there is scant agreement on what fairly qualifies as a “green job,” and much evidence that what policy-makers frequently consider “green jobs” are, in fact, existing jobs, belonging to the traditional economy, but simply reclassified as “green.” By emphasizing “green jobs,” policy-makers risk measuring environmental progress based on a concept that can often be entirely irrelevant, or worse, can actually be detrimental to both the environment and the economy. Too often, “green job” policies reward inefficiency, while also failing to distinguish between permanent, full-time jobs and temporary or part-time jobs. In some cases they can also discourage trade, limit or thwart competition, result in greater job losses elsewhere in the economy, and demand massive government subsidies, with some government “green job” programs requiring hundreds of thousands of dollars, or even millions, to create a single job. The urge of politicians to champion “green employment” is understandable given its convenient, if frequently unrealistic promise of a politically saleable anti-carbon policy. However, a more reliable and meaningful measure of environmental progress ultimately has little to do with the number of jobs a particular company creates (after all, if economic efficiency — and hence, prosperity — is indeed a policy goal, the number of jobs created should ideally be as minimal as necessary for every unit of output). Rather, if minimizing energy use and greenhouse gas emissions is the desired policy outcome, then measuring the intensity of energy use and greenhouse gas emissions per unit of output can be the only meaningful metric. It may not have the political appeal that a promise of “green jobs” does. But unlike “green jobs,” both of these measures provide quantifiable, non-arbitrary metrics of environmental performance and progress. In other words, unlike the problematic, arguably illusory concept of “green employment,” measuring energy-use intensity and emissions intensity actually tells us very clearly and reliably whether we are making the environment better or worse.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,803
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0020,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,040
Tête enseignante GPT0,250
Écart entre enseignants0,210 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission2
Résumé présentoui

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