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Record W3006316450 · doi:10.1002/tie.22123

Financing the circular economic model

2020· article· en· W3006316450 on OpenAlexaff
Anas Aboulamer, Khaled Soufani, Mark Esposito

Bibliographic record

VenueThunderbird International Business Review · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsDawson College
Fundersnot available
KeywordsExternalityUnobservableEconomicsScarcityIndustrialisationPopulationCapitalismFree marketProduction (economics)PovertyBusinessMarket economyMicroeconomicsEconomic growth

Abstract

fetched live from OpenAlex

Abstract Capitalism, as we know it, is the result of the industrial revolution, when resources were perceived as abundant and limitless. The population was much smaller and the environmental impact of the industrial activity was perceived as minimal. As the world population increased exponentially and more countries emerged from poverty to join the middle‐income rank, demand for products increased leading to a rapid industrialization with no concerns for its environmental and societal impact. Capitalism is also based on the idea of free markets that adjust automatically to new information about scarcity, demand, and processes of production to allocate resources in the most efficient way possible. However, free market implies that possibly unobservable factors are taken into consideration to lower the potential impact of negative externalities by imbedding them in the pricing process. Unfortunately, free markets failed in this task and the list of environmental disasters from the Gulf oil spill of BP, the tobacco health issue are good examples of the inability of the markets to gauge the impact of these negative externalities.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.061
GPT teacher head0.253
Teacher spread0.192 · 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 teacher head, not a consensus.

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

Citations13
Published2020
Admission routes1
Has abstractyes

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