Benefit from research involving non-probability samples
come up with an example on any criminal justice-related topic of your choice that would either require or benefit from research involving non-probability samples. Give a brief description of the phenomenon and your perspective on why it either cannot or should not be studied with larger, probability-based techniques. Why is the issue important to study, and what new insights could we expect using your approach?
Sample Solution
Phenomenon: Hidden Reentry Challenges Faced by Formerly Incarcerated Women
Description: Many formerly incarcerated women face unique challenges upon reentry into society, often beyond those experienced by men. These challenges can include issues related to childcare, domestic violence, and a lack of support networks specific to women.
Full Answer Section
Why Probability Sampling Isn't Ideal:- Underrepresentation: Women comprise a smaller percentage of the incarcerated population compared to men. A probability sample might not capture a sufficient number of women to provide robust data on their specific reentry experiences.
- Sensitivity of the Topic: Women may be reluctant to disclose sensitive details about their experiences (e.g., domestic violence) with strangers in a random survey.
- Snowball Sampling: Starting with a small group of formerly incarcerated women who have successfully reintegrated and asking them to refer others can help reach a wider network of women with diverse experiences. This allows researchers to build trust and rapport, potentially leading to more candid responses.
- Purposive Sampling: Recruiting women from organizations that specifically support formerly incarcerated women can ensure the sample reflects the target population of interest.
- The specific barriers women face in areas like childcare, housing, and employment.
- The prevalence of domestic violence and its impact on reentry success.
- The coping mechanisms and support networks women utilize to navigate reentry challenges.