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Modeling Energy Use and Technological Change for Policy Makers: Campbell Watkins’ Contribution as a Researcher-Practitioner

2008· article· en· W2084648678 on OpenAlexaff
Mark Jaccard

Bibliographic record

VenueThe Energy Journal · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsScope (computer science)Empirical researchEconomicsGovernment (linguistics)Energy (signal processing)Econometric modelWork (physics)Energy policyGreenhouse gasPublic economicsEngineeringComputer scienceEconometricsRenewable energy

Abstract

fetched live from OpenAlex

As an energy-economics modeler, who collaborated with academics while also consulting to government and industry, Campbell Watkins was especially interested in the empirical relationship between energy inputs and economic output. His skills were perfectly suited to this pressing research issue, which first emerged in the mid-1970s as the “energy-capital substitution” controversy. As his publication record shows, he worked with leading researchers in the development and econometric testing of dynamic specifications of this relationship. But he conducted this work always with a concern for how the research might be useful for immediate policy decisions. Today, the key policy question is the extent to which humanity can reduce its energy-related greenhouse gas emissions at reasonable cost. A new generation of “hybrid, top-down/bottom-up” models attempts to address the objectives Campbell listed in his widely circulated 1992 book chapter, particularly his point that technological change should not be treated as completely exogenous, but at least in part as a very long-run response to price changes and policies. But while current energy models are increasingly constructed to incorporate this feedback effect - notably those models used for simulating climate policies - the empirical estimation of their key parameters is still in its infancy. As Campbell noted in his characteristic dry humor, the scope for research remains “undiminished.” More hard-nosed researcher-practitioners like Campbell would certainly help.

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)0.001
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.299
GPT teacher head0.308
Teacher spread0.009 · 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 designTheoretical or conceptual
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
Published2008
Admission routes1
Has abstractyes

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