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Grand Transitions

2021· book· en· W4246666258 on OpenAlexaff
Vaclav Smil

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Abstract The modern world was created through the combination and complex interactions of five grand transitions. First, the demographic transition changed the total numbers, dynamics, structure, and residential pattern of populations. The agricultural and dietary transition led to the emergence of highly productive cropping and animal husbandry (subsidized by fossil energies and electricity), a change that eliminated famines, reduced malnutrition, and improved the health of populations but also resulted in enormous food waste and had many environmental consequences. The energy transition brought the world from traditional biomass fuels and human and animal labor to fossil fuel, ever more efficient electricity, lights, and motors, all of which transformed both agricultural and industrial production and enabled mass-scale mobility and instant communication. Economic transition has been marked by relatively high growth rates of total national and global product, by fundamental structural transformation (from farming to industries to services), and by an increasing share of humanity living in affluent societies, enjoying unprecedented quality of life. These transitions have made many intensifying demands on the environment, resulting in ecosystemic degradation, loss of biodiversity, pollution, and eventually change on the planetary level, with global warming being the most worrisome development. This book traces the genesis of these transitions, their interactions and complicated progress as well as their outcomes and impacts, explaining how the modern world was made—and then offers a forward-thinking examination of some key unfolding transitions and appraising their challenges and possible results.

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 categoriesInsufficient 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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.122
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1250.003

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 head0.007
GPT teacher head0.185
Teacher spread0.178 · 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

Citations48
Published2021
Admission routes1
Has abstractyes

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