Intimate partner violence in the Americas: a systematic review and reanalysis of national prevalence estimates
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.
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 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 | 0.024 | 0.072 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.028 | 0.026 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".