Bibliographic record
Abstract
This research study included 12 women - six who were in the process of obtaining their degree and six who had obtained their degree, for at least 10 years, from the same mid-sized Canadian university. All of the women were at least 30 years of age at the commencement of their program. This research study utilized qualitative interviews and examined the lived experiences of these 12 mature women for their experiences, barriers, and supports they encountered while obtaining their first undergraduate degree. The epistemological perspective, theoretical perspective, and methodology utilized were constructivism, feminism, and Charmaz’s constructivist grounded theory, respectively. The women identified both the barriers and the supports they experienced while in the process of obtaining their degrees. Some barriers they identified include multiple role strain, sexism, poverty, ineffective teaching methods, marginalization, health issues, circuitous paths to education, nonsupport for their specific needs, and programs that were not designed for the mature student along with uncertainty of how their programs might benefit them in the future. However, the women also identified male mentors as effective and supportive to their learning, which counters research examined that stated women learn more effectively from women mentors. The women also identified peers, family, and friend supports as important supports in their educational success. Other supports that were identified included receiving assistance for children, while the women attended to homework or classwork; assistance with more concrete chores (i.e., housework, groceries, editing papers); and supportive comments. Some of the women identified that a smaller campus environment supported them because they felt like they belonged and were a part of a family. These women identified the smaller campus as a major factor in their educational success. Workplace supports included flexible time off, financial assistance, and encouragement, these factors were also identified as major factors that assisted the women in their educational success. The women began their university program, either through self or other (i.e., friend, family member) guidance, to further develop as a person. The overarching goal, for the women, was that they wanted to “Make a Difference” in their lives and/or the lives of others. “Making a Difference” is the overarching, theme of this research, and it was this that kept the women motivated to continue through their degree program. A graphic model illustrates the women’s journey to their destination of “Making a Difference” through achieving their degree.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".