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Record W3204598495 · doi:10.3390/su131910617

A Systematic Literature Review of Inclusive Climate Change Adaption

2021· article· en· W3204598495 on OpenAlex
Ha Pham, Marc Saner

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsScope (computer science)Grey literatureContext (archaeology)Climate changePolitical scienceInclusion (mineral)United Nations Framework Convention on Climate ChangeSystematic reviewConventionSubsidyGovernment (linguistics)Adaptation (eye)Public relationsManagement scienceProcess managementSociologyComputer sciencePsychologySocial scienceBusinessGeographyEconomicsKyoto ProtocolLinguisticsEcology

Abstract

fetched live from OpenAlex

Inclusive approaches have been applied in many areas, including human resources, international development, urban planning, and innovation. This paper is a systematic literature review to describe the usage trends, scope, and nature of the inclusive approach in the climate change adaptation (CCA) context. We developed search algorithms, explicit selection criteria, and a coding questionnaire, which we used to review a total of 106 peer-reviewed articles, 145 grey literature documents, and 67 national communications to the United Nations Framework Convention on Climate Change (UNFCCC); 318 documents were reviewed in total. Quantitatively, the methodology reveals a slight increase in usage, with a focus on non-Annex 1 countries, gender issues, and capacity building. Qualitatively, we arranged the key insights into the following three categories: (1) inclusion in who or what adapts; (2) motivating inclusive processes; and (3) anticipated outcomes of inclusive CCA. We conclude, with the observation, that many issues also apply to Annex 1 countries. We also argue that the common language nature of the word ‘inclusive’ makes it applicable to other CCA-relevant contexts, including government subsidies, science policy, knowledge integration and mobilization, performance measurement, and the breadth of the moral circle that a society should adopt.

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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.654
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.050
GPT teacher head0.357
Teacher spread0.307 · 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