Violent Victimization against Women in Canada: Evidence from the General Social Survey 2009 Data, a Gendered Study
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
This study aimed to examine victimization against women in Canada. Statistics Canada General Social Survey (GSS) 2009 data set was used in this current study for the analysis. In all, 31,510 household were surveyed and out of that, 19,500 responses representing 61.6% were obtained for the GSS 2009, a sample which was smaller than the 24000 which was used for the 2004 general social survey. In this study, the short version of the GSS 2009 which has a sample of 1512 was used for the analysis. At the end of the study, it was revealed that there is no statistically significant difference regarding the experience of victimization in both males and females in Canada (p-value = 0.418, Lambda = 0.003, Phi = 0.21, Cramer’s V = 0.21. However, the results of the study revealed a significant difference the impacts of victimization of males and females respectively. Thus women are more likely to experience depression after being victimized than men (p-value = 0.000). Finally outcome of the study showed that respondents living in Urban neighborhoods were more likely to experience violent victimization than those in rural communities (Lambda = 0.000, Phi = 0.106, Cramer’s V = 0.106 and p-value = 0.000). The study therefore recommends that policies and programs to address violence against women need to be sustainable, properly financed, and parcipatory-involving not only women but men. Also comprehensive victim support systems are essential, ecompassing legal and counseling since the study indicated women experience more of the negative impacts after being victimized.
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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.007 | 0.001 |
| 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