New Frontiers Research Project - COVID and IPV
Bibliographic record
Abstract
Background: Globally one in three, or over 700 million, women experience violence perpetrated by an intimate partner. During the COVID-19 pandemic, a higher incidence and severity of IPV has been reported. Government-directed restrictions including stay-at home orders, physical distancing, and other pandemic-related measures forced many IPV organizations to roll back, adapt, or discontinue programs. While some community organizations developed new remote-service programs, others adapted existing models, and IPV organizations continue to provide virtual interventions to IPV survivors post-lockdown. Objectives: The overall objective of this study is to examine the innovative practices employed by community-based organizations that responded to intimate partner violence (IPV) and to assess the effectiveness of these services during the pandemic and pandemic recovery. Methods: Our study employs a mixed-method research design. The first and current phase involves in-depth interviews with frontline service providers and administrators of IPV service organizations across three countries (Canada, India, and South Africa). Interviews were audio-recorded and transcribed verbatim. Thematic analysis will be utilized. The second phase of this project includes a survey of service-engaged and non-service-engaged survivors in each country. Future Applications/Directions or for a completed study, Results/ Implications: As our study is in progress, suggested future directions include: 1) gathering insight that will inform future contingency plans for IPV service organizations during community-level disasters, such as COVID-19, 2) assessing the effectiveness of IPV existing and adapted interventions during the pandemic, and 3) to understand the resiliencies exhibited by IPV survivors with help-seeking during and following the COVID-19 pandemic.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.056 | 0.005 |
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".