Exploring effective academic advising for mature women : autobiography and personal vignettes based on interviews with seven mature female students and two academic advisors at a university in Montreal
Bibliographic record
Abstract
The purpose of this thesis was to explore the academic advising available to mature immigrant women over 45 years of age who return to university studies. In addition to my autobiographical account, I interviewed seven mature immigrant women enrolled in graduate studies and asked them about the role of academic advising in their choice of the university program to follow. I also interviewed two professional academic advisors in order to gain insight into their practice to meet the needs of this particular student group. The following themes emerged from the analysis of the data: Academic achievement was a product of very strong inner motivation combined with the support of families and friends. In turn, academic achievement helped women in improving their self-esteem and self-confidence which enabled them to achieve an important degree of satisfaction and self-realization. The results indicated that the majority of the women interviewed did not receive adequate academic advising and upon graduation they were not able to find jobs in the areas of their specialization. They also pointed to the importance of a humane, warm and friendly relationship with the academic advisor in order to disclose personal issues and get the needed help. Each one of the two academic advisors had a different approach to their practice. Nevertheless both advisors underlined the lack of university resources for in service education and upgrading of credentials. The results of this exploratory study point to the following recommendations: (a) The importance of providing career advising parallel to academic advising in order to help the students make choices which will lead to job opportunities upon graduation; (b) setting evening office hours for students who are employed full time during the day; (c) making available on the job education and training to academic advisors and faculty advisors in order to update their skills and knowledge to better advise mature immigrant women returning to university education.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".