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Record W2215604619

Climate Change Adaptation Challenges Facing New Brunswick Coastal Communities: A Review of the Problems and a Synthesis of Solutions Suggested by Regional Adaptation Research

2015· review· en· W2215604619 on OpenAlexaffabout
David J. Lieske, Lori Ann Roness, Emily A. Phillips, Mark A. Fox

Bibliographic record

VenueJournal of New Brunswick Studies / Revue d’études sur le Nouveau-Brunswick · 2015
Typereview
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsMount Allison University
Fundersnot available
KeywordsAdaptation (eye)Flood mythClimate change adaptationClimate changeFocus groupEnvironmental planningPoliticsEnvironmental resource managementPolitical sciencePublic relationsGeographySociologyPsychology
DOInot available

Abstract

fetched live from OpenAlex

Through a detailed examination of research conducted in Sackville, New Brunswick, this study synthesizes the findings of a series of focus groups and one-on-one interviews with the aim of achieving the following objectives: to identify and elucidate the important challenges related to climate change that New Brunswick coastal communities are currently facing; and to highlight solutions to these challenges. A number of key impediments are identified (e.g., low levels of community consensus) and the following solutions are proposed: to use flood risk visualization and software to aid adaptation planning; to ensure that high quality data are routinely gathered and shared; to build on ongoing community collaboration and communication; and to strengthen political and community leadership.

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)0.008
metaresearch head score (Gemma)0.009
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: Review · Consensus signal: Review
Teacher disagreement score0.857
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.016
Science and technology studies0.0020.002
Scholarly communication0.0060.004
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.382
GPT teacher head0.391
Teacher spread0.009 · 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
GenreReview

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

Citations9
Published2015
Admission routes2
Has abstractyes

Explore more

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