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Record W4405532526 · doi:10.1017/9781788216524.005

Shaping the future: a world after firepower

2023· other· en· W4405532526 on OpenAlexaff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsFirepowerGeographyArchaeology

Abstract

fetched live from OpenAlex

“The goal is not self-purification but structural change.” Leah Stokes, “A field guide for transformation” The discussion of fire and the matter of living in the Anthropocene keeps circling back to the question of what we make and how what we make shapes our landscapes and the planet as a whole. While environmental campaigns have frequently been about protecting landscapes and ecosystems from damage due to industrial activities, and these remain important, the bigger questions raised by the Anthropocene focus on production. It's all about what we make, and crucially what what we make does to the Earth system, to invoke Foucault's phrase once again. Fire has allowed us to change our habitats dramatically. But while fossil fuels have made some parts of humanity wealthy it is clear that we cannot go on using them the way we have done for the last couple of centuries. The Green New Deal idea, some of the policies which were partially incorporated into the US 2022 Inflation Reduction Act, suggests making very different things for a society that is fairer and one that can survive in the long term. Humanity cannot go on using firepower without constraint both because of the dangers of climate change, and because of pollution from plastics and all the destruction that the current combustive mode of economy entails. Lobbying and attempts to change public policy have only worked up to a point. Other strategies are clearly needed as the activists in climate strikes, tyre extinguishers and many other campaigns are reminding us daily. Clearly, humanity is making far too much carbon dioxide. Which in turn raises the question who decides what gets made? Investment is central here as divestment activists have figured out; money spent on pipelines and oil wells isn't money spent on solar panels. Money invested in making internal combustion engines isn't going to make batteries or electric motors. Funding, as provided for in the Inflation Reduction Act, to make and install heat pumps in American homes has the potential to speed up the electrification of heating and in the process use energy much more efficiently. Comfortable houses, reduced electricity bills and less climate disruption all go together.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0150.024
Scholarly communication0.0150.024
Open science0.0010.007
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0140.002

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 head0.096
GPT teacher head0.447
Teacher spread0.351 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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