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Record W7115308782

Ilmastonmuutokseen sopeutuminen Itämeren ja Arktisen alueen maissa : Sopeutumispolitiikka ja -hallinto)

2021· other· en· W7115308782 on OpenAlexaboutno aff

Bibliographic record

VenueDoria (University of Helsinki) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptation (eye)Corporate governanceStakeholderWork (physics)Action (physics)Climate change adaptationSet (abstract data type)Context (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

The objective of this study was to collect and synthesise information about climate adaptation policy and governance in the Baltic Sea and Arctic regions. The report also describes best practices from different countries that Finland could learn from and gives recommendations for Finland. The countries and territories included are Sweden, Denmark, Faroe Islands, Greenland, Norway, Iceland, Germany, Poland, Estonia, Latvia, Lithuania, Russia, Belarus, Canada, and the USA. The report is based on a literature study on the situation of adaptation planning and coordination in the target countries and regions. Document review was complemented with interviews of national experts. Broadly speaking, western, bigger and Nordic countries as well as those that started early have more advanced adaptation policies and governance. The studied countries and regions show both similarities and differences in approaches. Five have both a national adaptation strategy and plan, two have only a strategy, and two have only a plan, and five do not have such a document yet. Some countries have integrated both mitigation and adaptation in the same strategy. On sectoral adaptation work, the approach differs from mandatory sectoral action plans to no separate sectoral adaptation documents at all. The most common approach in regional and local adaptation work is that subnational adaptation strategies are voluntary, but they are supported by projects. However, regional or local adaptation plans are obligatory in some countries. Countries use national adaptation strategies and action plans to set priorities. The processes for setting the priorities vary, but may involve inter-ministerial committees, expert working groups, stakeholder dialogues and public consultations. Priorities often cover different sectors and cross-cutting measures (e.g. information). Several countries want to integrate adaptation into existing processes and governance levels. The biggest challenges in adaptation policy cluster around three issues: the need to improve awareness and political priority of adaptation; challenges in coordination across sectors and levels; as well as lack of funding or human resources dedicated for adaptation.

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 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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient 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 score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0700.008

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 head0.018
GPT teacher head0.218
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; both teacher heads 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
Published2021
Admission routes1
Has abstractyes

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