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Transfer of Technology as an International Bridge for Sustainable Development: Issues for Developing Countries

2023· article· en· W4389975723 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal For Multidisciplinary Research · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsnot available
Fundersnot available
KeywordsSustainable developmentKyoto ProtocolAdaptation (eye)Bridge (graph theory)Developing countryBusinessClimate changeEnvironmental planningPolitical scienceEnvironmental resource managementEnvironmental economicsEconomic growthEconomicsEnvironmental scienceLaw

Abstract

fetched live from OpenAlex

For equitable and appropriate measures needed for Sustainable Development, technology transfer works as a bridge in bilateral and multilateral agreements. The concept needs to clarify the Principle of Sustainable Development based on Common but Differentiated Responsibilities, accessibility and affordability, capacity building, resilience, adaptation as well as mitigation. Policies and Regulations regarding technology transfer discussed in the Montreal Protocol and Kyoto Protocol are significant. As climate change becomes the current problem, ESTs have drawn the attention of the UNFCCC. The fundamental challenges before the world are social disparities, degradation of soil, and depletion of water and natural resources. Technology transfer works as the platform for interaction between developed nations and developing nations to achieve Sustainable Development. A case study of Taiwan is reflected to explain the situation prevailing for countries that are not within the limits of the International Court of Justice or the UNFCCC. Overall, the transfer of technology has been the most crucial factor in maximizing trust and reducing tension to overcome the problem of climate change and other issues associated with it.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.103
GPT teacher head0.473
Teacher spread0.370 · 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