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Record W7031855653

9781000409741.pdf

2023· other· en· W7031855653 on OpenAlexaboutno aff

Bibliographic record

VenueOAPEN (The OAPEN Foundation) · 2023
Typeother
Languageen
FieldEngineering
TopicSustainable Design and Development
Canadian institutionsnot available
Fundersnot available
KeywordsTemporalitiesTemporalityJournalismClimate changeNegotiationPoliticsInscribed figureClimate justice
DOInot available

Abstract

fetched live from OpenAlex

This edited collection addresses climate change journalism from the perspective of temporality, showcasing how various time scales—from geology, meteorology, politics, journalism, and lived cultures—interact with journalism around the world. Analyzing the meetings of and schisms between various temporalities as they emerge from reporting on climate change globally, Climate Change and Journalism: Negotiating Rifts of Time asks how climate change as a temporal process gets inscribed within the temporalities of journalism. The overarching question of climate change journalism and its relationship to temporality is considered through the themes of environmental justice and slow violence, editorial interventions, ecological loss, and political and religious contexts, which are in turn explored through a selection of case studies from the US, France, Thailand, Brazil, Australia, Spain, Mexico, Canada, and the UK. This is an insightful resource for students and scholars in the fields of journalism, media studies, environmental communication, and communications generally.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.075
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0110.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.9250.871

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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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