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Energy Geography

2004· book-chapter· en· W4239735435 on OpenAlexaboutno aff
Barry D. Solomon, Martin J. Pasqualetti

Bibliographic record

VenueOxford University Press eBooks · 2004
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsnot available
Fundersnot available
KeywordsFossil fuelDominionPopulationNatural resource economicsIndustrial RevolutionGeographyPolitical scienceEconomicsEngineeringSociologyLawDemography

Abstract

fetched live from OpenAlex

Fossil fuels powered the Industrial Revolution and they continue to dominate our lives as we enter the twenty-first century. Yet there are clear signs that the grip they have on every sector of society must soon relax in favor of other energy sources. Such a transition will not come because we are running out of fossil fuels, but rather because the environmental and social costs of their rapid use threaten our very existence on the planet. This is an expected development. From the time when fossil fuels first enabled and magnified humans’ dominion over the earth, the costs they brought—as any good economist would argue—have been inseparable from their benefits. Although the benefits were explicit and the local costs were experienced by many, it was not until skilled writers such as Zola, Orwell, Llewellyn, and Dickens vividly portrayed them that their widespread and pernicious nature was broadcast to those outside their immediate reach. Nowadays the problems we are grappling with have spread to the global scale, including atmospheric warming, thinning ozone, and rising exposure to above-background radioactivity. Understanding earth–energy associations is a task well matched to the varied skills of geographers. The worth of such study is increasingly apparent as the world’s human population continues to rise, as fossil fuels become more difficult to wrest from the earth, and as we continue to realize that there will be no risk-free, cost-free, or impact-free rabbits coming out of the alternative energy hat. In this chapter, we review developments in energy geography in the US and Canada as posted to the literature since the first edition of Geography in America, including a sprinkling from overseas to provide context. Owing to the fundamental nature of energy, we have accordingly cast a wide net in our background research, albeit with some boundaries. For example, while we discuss several important contributions to energy research by physical and environmental geographers, we excluded consideration of such themes as energy budgets, most climate change research, and mine-land reclamation and radioactive waste transport studies by hydrologists and geomorphologists.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.958
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.017
GPT teacher head0.216
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; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations4
Published2004
Admission routes1
Has abstractyes

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