Bibliographic record
Abstract
There is a serious crisis in education.Students often do not want to learn and teachers do not want to teach.More than ever before...educators are compelled to confront the biases that have shaped teaching practices in our society and to create new ways of knowing, difference strategies for the sharing of knowledge.We cannot address this crisis if progressive critical thinkers and social critics act as though teaching is not a subject worthy of our regard.-bell hooks, Teaching to Transgress.Whoever teaches learns in the act of teaching, and whoever learns teaches in the act of learning.-Paulo Freire, Pedagogy of Hope.It was a decision whose time had come: in January 2012, I left a wellpaid job in the union movement.After seven years, I felt disconnected from labour's activist base; in general, my work involved meetings with union officials, and overseeing large projects.Those efforts, while useful in some respects, fell short of my own pedagogical expectations.I had learned valuable administrative skills, but wanted more exposure to a classroom setting as well as learning opportunities with students and fellow educators.I wanted to change my situation, so a new set of circumstances could change me.1
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 | 0.024 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.064 |
| Scholarly communication | 0.029 | 0.060 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.025 | 0.046 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".