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Record W4400734226 · doi:10.1111/faam.12409

Making sense of climate change in central government annual reports and accounts: A comparative case study between the United Kingdom and Norway

2024· article· en· W4400734226 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFinancial Accountability and Management · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsnot available
FundersQueen's UniversityUniversitetet i AgderQueen's University BelfastKlima- og miljødepartementetGovernment of the United Kingdom
KeywordsClimate changeGovernment (linguistics)Political scienceRegional scienceGeography

Abstract

fetched live from OpenAlex

Abstract Taking a sensemaking and accountability perspective, this paper explores how the Norwegian and the United Kingdom (UK) central governments understand climate change in the annual reports and accounts and how this shapes its accountability. Using a thematic analysis, we find that the Norwegian central government makes sense of climate change as a global problem requiring coordinated actions with shared responsibility and accountability to international agreements. In contrast, the UK central government understands climate change as a problem for individual departments and accountability to national guidelines. Sensemaking is enabled primarily in the narratives but also visually in the UK central government. Our research contributes to climate‐related and accounting research by illustrating how central government understands climate change. Theoretically, we extend the literature on sensemaking to the public sector and how sensemaking shapes accountability for climate change.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.376
GPT teacher head0.459
Teacher spread0.083 · 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