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Record W151471770

Oil's History of Booms and Busts: Toward the Ultimate Downturn

2006· article· en· W151471770 on OpenAlexaboutno aff
C. J. van der Veen

Bibliographic record

VenueThe Knowledge Bank (The Ohio State University) · 2006
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsBoomEconomicsRecessionKeynesian economicsBusinessGeologyOceanography
DOInot available

Abstract

fetched live from OpenAlex

It is often said that we learn from our mistakes. This may be true for individuals, but collectively, humanity repeatedly continues to exhibit collective amnesia and, by ignoring past events – willfully or not – the same mistakes continue to be made. A case in point may be our continued dependence on and consumption of fossil fuels, most notably oil and natural gas. Since the discoveries of oil fields in the upper mid-west of the United States and in southern Ontario, the world economy has become truly dependent on this black gold, led, of course, by a handful of oil-thirsty industrialized nations. Yet most western consumers appear to have little concern about the available resources and how limited these resources are – much like in the early days of the American and Canadian oil boom. Recoverable oil reserves are limited – certainly the end of cheap oil is in sight, if not here already. This may not necessarily imply the end of civilization as we know it, but surely the decline in world oil production will necessitate changes in our way of life and thinking. Perhaps most surprising is the fact that many smaller communities have experienced their local “peak oil” and gone from boom to bust – yet, many people, including most politicians, continue to be optimistic and hope for some magical solution to our problems. As argued in this report, what has happened on smaller scales to the towns of Petrolia, PA, ON, TX, CA, and too many other communities in the original heartlands of oil exploration, is bound to replay on the world stage. This time around, however, there may not be an easy way out.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.013
GPT teacher head0.212
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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2006
Admission routes1
Has abstractyes

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