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Record W4401288040 · doi:10.21275/sr24731024215

The Dynamics of the Knowledge - Based Economy: Innovations, Challenges, and Future Time - Based Economy

2024· article· en· W4401288040 on OpenAlexaff
Dragos Seuleanu

Bibliographic record

VenueInternational Journal of Science and Research (IJSR) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsKnowledge economyEconomicsInformation economyDigital economyEconomic systemEconomyComputer science

Abstract

fetched live from OpenAlex

Peter Drucker's concept of a knowledge -based economy remains relevant as it emphasizes the significance of advanced scientific research in driving innovation and economic growth. This paper explores methods to accelerate innovation and addresses the critical distinction between innovation and knowledge. By examining the roles of various industries and the evolution of economic sectors, the paper highlights the importance of continuous knowledge flow for entrepreneurship and innovation. The discussion extends to the potential of the quinary economy and the future implications of knowledge transfer and weaponization. The paper concludes with strategic recommendations for enhancing knowledge resilience, leveraging knowledge for national and international competitiveness, and preparing for the next stage of economic evolution: the time -based 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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.063
GPT teacher head0.406
Teacher spread0.343 · 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 designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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