Book Review: <i>Seeking Wisdom in Adult Teaching and Learning: An Autoethnographic Inquiry</i> , by W. Fraser
Bibliographic record
Abstract
In preparing to write this review on Wilma Fraser's book, Seeking Wisdom in Adult Teaching and Learning, I decided to invite one of my graduate students, Elizabeth Tingle, to engage in this process with me.I realized, while reading this book, I was close to the age of the author and I have also lived many of the changes she has experienced as an adult educator, both within the university and at the broader societal level.Indeed, even though I reside on the other side of the Atlantic Ocean here in Canada, I could certainly relate to her stance when she acknowledges that while is she searching for wisdom, "the tone of this narrative is coloured by a profound sense of loss at many levels" (p.141).However, she also indicated that it was important to "collectively inspire hope and courage across our departments and faculties; and to pay particular attention to the metaphors we use in our teaching and learning environments so that we can foster alternative narratives of openness " (p.190).And so, I began to wonder what it would be like to read this book from the perspective of someone who, while having significant experience as a community adult educator, is fairly new to discourses of adult education.In essence, as she stands at the beginning of the road as an academic, what wisdom is she garnering from the author, someone I would associate as being an elder academic?We now turn to Elizabeth and her commentary on Fraser's book.As a first year MA student in adult education, I have more questions than answers.While I have some educational background as a former secondary teacher, the theory and history of the discipline of adult education is new terrain for me.During my first course with Dr. Groen, I was inspired and excited about the field I was joining; I love how expansive, radical, and inclusive adult education can be.Surely, the adult educator is vital in a world where constant learning is needed and celebrated.And yet, this excitement and optimism has been somewhat dimmed as I conclude my first year of coursework and prepare to write my thesis.I have even wondered: Have I entered a dying field?Wilma Fraser, in her autoethnographic inquiry Seeking Wisdom in Adult Teaching and Learning provides the perspective and insight of someone at the opposite end of my current journey.Fraser wrote about her "pilgrimage" (p.11) to seek for wisdom as she retired from the field of adult education, and so takes 889579A EQXXX10.
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.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.009 |
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".