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Record W797461911

"Climate Power Play: Financial, Legislative, and Regulatory Moves toward a New Energy Economy": Time to Wake Up on Climate Change

2014· article· en· W797461911 on OpenAlexaboutno aff
Senator Sheldon Whitehouse

Bibliographic record

Venue˜The œAmerican University law review · 2014
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsLegislatureClimate changePower (physics)ConversationState (computer science)LawPleasureState legislaturePolitical scienceHistorySociologyPsychology
DOInot available

Abstract

fetched live from OpenAlex

Thank you for inviting me to speak at today's Symposium, Power Play: Financial, Legislative, and Regulatory Moves Toward a New Energy Economy.1 I come from Rhode Island, where we take our environment and our state nickname-the Ocean State2-very seriously. This was perhaps best exemplified by an exchange between Senator Theodore Francis Green,3 a Rhode Island Senator of great longevity, and one of his Senate colleagues. Green had apparently done something to annoy a fellow Senator, who then turned to him and said, Theodore, how big is that little state of yours anyway? Green looked coolly back at him and said, Well, that would depend wouldn't it-high tide or low tide?My point here is that what's happening out there, particularly in our oceans, means a lot for Rhode Island, and that makes it a real pleasure for me to be here with you to have this conversation about climate change. I am perhaps the most optimistic person in the Senate-perhaps the most optimistic person in Congress-about our ability to get something done on this issue. And let me take a few minutes here to take you through my case.The first point in the case is that the reality of climate change is really now beyond serious or sober questioning.4 The atmosphere is measurably warming,5 Arctic ice is visibly melting,6 seas are warming and rising and acidifying,7 and these are not complex projections. They're not computer models. They are measurements. And they are measurements that can be made relatively simply.We also know how much harm the reality of climate change is causing. And we see its costs all around us. We see it in storm-damaged homes and flooded cities.8 We see it in drought-stricken farms and raging wild fires.9 We see it in bleaching coral10 and stressed shellfish.11 We see it in shifting habitats12 and migrating diseases.13These costs are not, however, being incorporated into the price of the coal or oil that are contributing to climate change by releasing carbon pollution when burned. The big oil companies and the coal barons have managed to offload all of those costs onto the rest of us-onto society.14 That is wrong, and it is also a market failure. It gives polluting industries an unfair advantage over cleaner energy producers.So that is why I'm working with a number of colleagues to put a price on carbon pollution-an accurate price on carbon pollution.15 The idea is a pretty simple one: the big polluters pay a fee to the American people to cover the cost of dumping their waste into our atmosphere and oceans.16At present, I will concede that political conditions in Washington do not make that possible. So what do we have to do then? We have to change those political conditions. I think we can do this, and I think we can do it more quickly than most people realize. I see the path before us; I see the tools to do it with, and it's up to us to pick up those tools and use them.I'll mention three of them.The first tool is one that's actually already been wielded, and I give President Obama credit for this. His Climate Action Plan17 has a particular strength to it, which is that the Environmental Protection Agency will be setting carbon pollution standards for new and existing power plants.18The worst fifty power plants in the United States pump out more carbon pollution than Canada.19 They pump out more carbon pollution than South Korea.20 So setting standards to limit pollution from these plants is a big deal. Now, when the owners of those power plants see those regulations and the associated costs of compliance coming at them, suddenly, an economy-wide carbon fee may look a little better. When their status quo is no longer that they get to pollute for free, their attitude about negotiating carbon legislation may shift. And when the polluters' attitude shifts, the Republican Party's attitude shifts.Think about it: if you're a practical politician representing a coal state, you have to realize that the jobs and revenue provided by that industry won't last forever. …

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.020
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0170.011
Scholarly communication0.0170.018
Open science0.0020.007
Research integrity0.0150.024
Insufficient payload (model declined to judge)0.0190.004

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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2014
Admission routes1
Has abstractyes

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