Examining Gender Responsive Implementation of National Climate Change Policies
Bibliographic record
Abstract
Globally, there is a growing recognition of implementing gender considerations into national climate change policies and actions. However, examining climate policies at the domestic level remains an under researched topic. The aim of this study is to investigate if countries are reflecting gender equality concerns and the linkages between climate change within their Nationally Determined Contributions (NDCs) and National Communications (NCs) (both of which are national climate change policies) in a gender responsive manner. Through the literature review, which incorporates feminist perspectives, this research identifies five key concepts that can contribute to the gender responsive implementation of climate change policies. The following five concepts were used to build the gender responsive criteria: human rights, gender equal participation, power relations, gender mainstreaming and budgeting. Using the gender responsive criteria, I performed thematic analysis of six countries (Brazil, Canada, Egypt, Finland, Indonesia and Sweden) NDCs and NCs. The thematic analysis revealed various findings regarding the reflection of gender responsive implementation in the policies analyzed. Several data extracts displayed multiple connections with the gender responsive criteria, however the majority of the NDCs and NCs did not incorporate gender responsive concepts consistently throughout the policies. Much of the language pertaining to gender was geared towards empowering girls and women in developing countries; frequently positioned women as vulnerable in the context of climate change and often discussed gender in relation to adaptation and disaster reduction strategies. Such findings were anticipated as these issues are highlighted across the gender and climate change policy literature. However, the results from the analysis provided useful insights on the current situation on gender responsive implementation in NDCs and NCs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".