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Record W4394976793 · doi:10.1007/978-3-031-56560-1_11

UN’s SDGs 2030 Agenda, Environment as Global Public Good

2024· book-chapter· en· W4394976793 on OpenAlexaff
Özay Mehmet, Vedat Yorucu

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsCarleton University
Fundersnot available
KeywordsPolitical scienceEnvironmental planningEnvironmental science

Abstract

fetched live from OpenAlex

This Chapter adopts an idealistic perspective to discuss the UN’s Sustainable Development Goals (SDGs) dealing with two questions: (1) How can these noble goals be financed? and (2) Where to start implementation? It is argued that SDGs cannot be achieved without provision for their financing. An ideal world is a just world without poverty and hunger, with peace and security, there is human dignity for all, with access to health, education, housing, and all other basic human needs. In such an ideal world, every individual counts. There is entitlement to a universal basic income (UBI). If cash payment is not feasible for political or economic reasons, an equivalent investment in creating a just and sustainable world should be considered. Our global ecosystem is an intricately balanced global public good (GPG) for the collective benefit of humanity. Diverse species in forests, seas and on land are inter-dependent, co-existing in a delicate support system. Rain, sunshine and labor support agriculture and food production, industry provide goods and services, while good governance ensures health, safety, and other basic human needs. It all fits together like a complex machine. When a single component is damaged, the whole malfunctions. Poverty and Climate change are the top man-made damage in our world today. Sustainability, a global strategy to keep the system in good order, is now a global challenge.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.641
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2460.196

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 head0.014
GPT teacher head0.213
Teacher spread0.199 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2024
Admission routes1
Has abstractyes

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