Patriarchy at the helm of gender-based violence during COVID-19
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.
Bibliographic record
Abstract
Gender-based violence (GBV) or violence against women and girls (VAWG), is a global pandemic that affects 1 in 3 women in their lifetime and VAWG is one of the most prevalent human rights violations in the world. The high level of investment going into the COVID-19 recovery plan is a unique opportunity to reshape our patriarchal society, to coordinate across sectors and institutions and to take measures to reduce gender inequalities. Relief efforts to combat the pandemic should take the needs of the vulnerable population, particularly women and girls afflicted by GBV into consideration, as their needs were mostly ignored in the recovery plan of Ebola. GBV is linked to dominance, power and abuse of authority or because any calamity, be it a pandemic, conflict or a disaster. This will further exacerbate pre-existing gendered structural inequalities and power hierarchies as protective mechanisms fail leaves women and girls more vulnerable, fueling impunity for the perpetrators. There is a need for international and domestic violence prevention policies to not only focus on narrowly defined economic or political 'empowerment' because that is insufficient when it comes to challenging existing gender inequalities. Incorporating an individual's religious beliefs and community of faith (mosque, church, temple or synagogue) can offer a support system for an individual and her/his family amid a public health crisis. There is a need to engage men and boys by tailoring messages to challenge gender stereotypes and unequal gender roles to overcome patriarchy.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it