When parents go to school: Challenges and enablers for students who combine parenting and post-secondary education
Bibliographic record
Abstract
This study builds on existing descriptive research about student parents and mature students (Holmes, 2005; Sweet & Moen, 2007) in order to better understand the experiences of people who combine parenting and post-secondary education (PSE) in Canada. The goal of this research was to inform individual, institutional, and government practices and policies to enhance parents' abilities to combine school and family roles. The research addressed two main questions: 1) Does parental status relate to participation in and completion of college and under-graduate university programs? 2) In what ways does parental status relate to participation in college and under-graduate university programs? A mixed methods approach was employed that integrated thematic analysis of semi-structured interviews with 40 student parents and secondary analyses of two Canadian national data sets, the Survey of Labour and Income Dynamics (SLID) and the Youth in Transition Survey (YITS). For this study, student parents were defined as college or undergraduate university students who had physical custody of one or more children under the age of 18. Logistic regression models suggested that parenthood is negatively related to participation and completion of PSE for young parents and associated with lower probability of participation but not necessarily lower probability of completion for parents when a broader age range (16-59) is considered. Models also suggested different effects related to demographic variables such as marital status and labour force status for parents and nonparents. Analysis of the interviews provided information about the ways in which parental status may affect PSE participation. The results are described with respect to four categories: 1) challenges related to being a student parent, 2) enablers for combining school and family roles, 3) strategies to manage school and family roles, and 4) perceived benefits of being a student parent. Numerous themes emerged within these categories and higher level analysis yielded six areas of influence that were reflected across categories: finances, child care, time, fit with the institutional culture, effects on personal well-being, and effects on family relationships.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".