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Record W1537221527

Innovation and Growth in the Knowledge-based Economy

2000· article· en· W1537221527 on OpenAlexaff
Anastassios Gentzoglanis

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsKnowledge economyEconomic systemBusinessEconomicsEconomic geographyIndustrial organizationEconomy
DOInot available

Abstract

fetched live from OpenAlex

If capital stock is considered in a broad sense, to include both physical and intellectual capital, the law of diminishing returns may not apply and the higher the investments in intangible assets the higher a country's growth rate.The so-called AK growth models by taking into account both tangible and intangible capital do succeed to establish a positive relationship between growth rate and the capital stock.The empirical studies confirm this relationship but they fail to make an explicit account of the contribution of intangible capital to growth.This stems from the fact that lots of investments in intellectual capital and other intangible assets are not counted as such in national income and product accounts.The development of the AK models help to identify the neglected elements of growth and show the importance of taking them explicitly into account in order to better explain the current growth rates of the new economy.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score0.983

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.203
Teacher spread0.185 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2000
Admission routes1
Has abstractyes

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