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Record W7010694580

Is it just hot air?: the security discourse on climate change

2009· dissertation· en· W7010694580 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2009
Typedissertation
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
FundersEuropean CommissionDirektoratet for UtviklingssamarbeidWorld Health OrganizationMinistère de la Défense NationaleU.S. Department of Defense
KeywordsClimate changeArgument (complex analysis)Vulnerability (computing)State (computer science)Divergence (linguistics)National security
DOInot available

Abstract

fetched live from OpenAlex

Abstract: There is a near-consensus among governments, scientists, and the media that climate change poses a genuine threat to state security. Despite this consensus, the results of cooperative efforts to deal with this threat have been unimpressive. This thesis attempts to explain the divergence between the discourse on climate change and state behaviour by constructing a neorealist theory of cooperation on climate change. The argument comprises two central hypotheses. First, as the vulnerability of a state to climate change increases, it will be more willing to cooperate. Second, as the military threat to national security decreases, states will be more willing to cooperate. These hypotheses are supported by secondary hypotheses that posit a relationship between system-level variables and the level of cooperation. Statistical methods are used to test these propositions. The results do not support the hypothesized relationships.

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)0.011
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.024
Scholarly communication0.0100.007
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.058
GPT teacher head0.332
Teacher spread0.274 · 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
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
Published2009
Admission routes1
Has abstractyes

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