MétaCan
Menu
Back to cohort
Record W4240021339 · doi:10.1787/91355ac8-en

Clifton to Tangoio Coastal Hazards Strategy 2120, Hawke’s Bay, New Zealand

2019· book-chapter· en· W4240021339 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

VenueOECD eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEarthquake and Disaster Impact Studies
Canadian institutionsnot available
FundersNatural Resources CanadaDalhousie University
KeywordsBayOceanographyGeographyGeology

Abstract

fetched live from OpenAlex

This chapter describes the process behind the Clifton to Tangoio Coastal Hazards Strategy 2120, a process led by a partnership of local communities. The case study illustrates how various stakeholders can work collaboratively to take long-term decisions on complex and uncertain challenges, how the dynamic adaptive planning pathways method can work in practice, and the importance of open conversations about accountability and responsibility.This chapter was written by Emma Corbett, Ministry for the Environment and Simon Bendall, Mitchell Daysh Limited.Acknowledgments: Thanks to the Hawke’s Bay Regional Council, Hastings District Council and Napier City Council for their support in the development of this case study.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.549
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.004

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 head0.038
GPT teacher head0.304
Teacher spread0.265 · 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