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Record W7056825002

Gender and climate change : women matter

2011· report· en· W7056825002 on OpenAlexfundno aff

Bibliographic record

VenueEconomic Commission for Africa Knowledge Repository (Economic Commission for Africa) · 2011
Typereport
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersInstitut Alam Sekitar dan Pembangunan, Universiti Kebangsaan MalaysiaAfrican Union CommissionDepartment for International DevelopmentEuropean CommissionInternational Development Research CentreAfrican UnionInternational Fine Particle Research InstituteUnited Nations Development ProgrammeAfrican Development Bank Group
KeywordsClimate changeVulnerability (computing)Dimension (graph theory)Adaptation (eye)Political economy of climate changeSustainable developmentAdaptive capacityClimate change mitigationSustainability
DOInot available

Abstract

fetched live from OpenAlex

This paper seeks to draw attention to the gender dimension of climate change and the need to integrate gender issues in climate change responses, with particular emphasis on women’s concerns. The paper is divided into four sections. The first highlights the inevitability of climate change, its impact on the poor and vulnerable, its implications for sustainable development and the need for effective adaptation and mitigation measures. It also underscores how climate change disproportionately affects women and what needs to be done to ensure that women’s concerns are adequately addressed. The second looks at how climate change impacts on key climate-sensitive sectors, the gender dimension of the impacts, and proffers recommendations on what should be done to reduce the vulnerability of women to these impacts, and enhance their adaptive capacities. The third provides an overview of financing and capacity building initiatives that could be accessed to fund adaptation and mitigation programmes and projects. The final section makes concluding remarks on the basis of the findings of the preceding sections.

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)0.002
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 categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.113
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0640.001

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 head0.080
GPT teacher head0.306
Teacher spread0.226 · 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
Published2011
Admission routes1
Has abstractyes

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