Sustainable Development Goals and Gender Equality: A Social Design Approach on Gender-Based Violence
Bibliographic record
Abstract
Gender equality is a central human aspect of the Sustainable Development Goals. Among its multiple and complex issues, this research highlights gender-based violence as a domain that affects women’s empowerment and the guarantees of an effective equality on numerous levels. To address such a complex structure, which perpetuates inequalities between men and women, generating multiple effects and jeopardising social changes, social design can provide contributions on cultural and social levels. To achieve social systemic changes, one needs to activate profound cultural transformations. Thus, how can we change culture without rejecting the need to empower women and promote equality? The Montréal Design Declaration (2017) recognised social design’s potential to achieve the Sustainable Development Goals (SDG), to contribute to global challenges, and to accept a calling for stakeholders’ integration and agency promotion. This review explores how social design can provide contributions with regard to SDG5 and gender-based violence, presenting relevant domains that actively contribute to cultural transformation to address interventions in this systemic phenomenon.
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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 | 0.029 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.034 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".