Advances in Research on Teaching
Bibliographic record
Abstract
Citation (2012), "Advances in Research on Teaching", Isabelle Young, M., Joe, L., Lamoureux, J., Marshall, L., Dorothy Moore, S., Orr, J.-L., Mary Parisian, B., Paul, K., Paynter, F. and Huber, J. (Ed.) Warrior Women: Remaking Postsecondary Places through Relational Narrative Inquiry (Advances in Research on Teaching, Vol. 17), Emerald Group Publishing Limited, Bingley, p. iii. https://doi.org/10.1108/S1479-3687(2012)0000017019 Publisher: Emerald Group Publishing Limited Copyright © 2012, Emerald Group Publishing Limited Book Chapters Warrior Women: Remaking Postsecondary Places through Relational Narrative Inquiry Advances in Research on Teaching Advances in Research on Teaching Copyright Page Testimonials Acknowledgements Dedication Group Photo from Winnipeg Fall 2008 Foreword to Warrior Women Not Tomorrow … Today Introducing Ourselves: Storied Experiences Shaping the Stories We Live By Co-Composing Relational Narrative Inquiry Reclaiming and Maintaining Our Aboriginal Ancestry Reclaiming Our Ancestral Knowledge and Ways: Aboriginal Teachers Honouring Children, Youth, Families, Elders, and Communities as Relational Decision Makers Becoming “Real” Aboriginal Teachers: Counterstories as Shaping New Curriculum Making Possibilities Being Included in and Balancing the Complexities of Becoming an Aboriginal Teacher Sharing Our Forward Looking Stories References Learning to See the Little Girl in the Moon: An Afterword to Warrior Women About the Contributors
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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.085 | 0.042 |
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".