Intimate partner violence in the Americas: a systematic review and reanalysis of national prevalence estimates
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
<bold>Objectives.</bold>To describe what is known about the national prevalence of intimate partner violence (IPV) against women in the Americas across countries and over time, including the geographic coverage, quality, and comparability of national data. <bold>Methods.</bold>This was a systematic review and reanalysis of national, population-based IPV estimates from 1998 – 2017 in the Americas. Estimates were reanalyzed for comparability or extracted from reports, including IPV prevalence by type (physical; sexual; physical and/or sexual), timeframe (ever; past year), and perpetrator (any partner in life; current/most recent partner). In countries with 3+ rounds of data, Cochran-Armitage and Pearson chi-square tests were used to assess whether changes over time were significant (<italic>P</italic>< 0.05). <bold>Results.</bold>Eligible surveys were found in 24 countries. Women reported ever having experienced physical and/or sexual IPV at rates that ranged from 14% – 17% of women in Brazil, Panama, and Uruguay to over one-half (58.5%) in Bolivia. Past-year prevalence of physical and/or sexual IPV ranged from 1.1% in Canada to 27.1% in Bolivia. Preliminary evidence suggests a possible decline in reported prevalence of certain types of IPV in eight countries; however, some changes were small, some indicators did not change significantly, and a significant increase was found in the reported prevalence of past-year physical IPV in the Dominican Republic. <bold>Conclusions.</bold>IPV against women remains a public health and human rights problem across the Americas; however, the evidence base has gaps, suggesting a need for more comparable, high quality evidence for mobilizing and monitoring violence prevention and response.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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