Bibliographic record
Abstract
This book is grounded in the idea that words matter. It holds that how we discuss teachers and teaching in the public space shapes the way we come to regard teachers as a society; the beliefs we hold about who they are, what they do, and why they do it. Over time it also comes to shape the conditions and contexts in which teachers do their work. This matters because schooling provides one of the very few common experiences that most of us share. Teaching, in particular, provides a convenient rallying point for discussions of public policy, and beyond citizens’ own school experiences, the print media makes the most significant contribution to broad social understandings of schooling and teachers’ work. This book provides a comprehensive and systematic exploration of print media discourses around teachers and their work, using over 65,000 articles published in Australian print media from 1996 to 2020 as a case study. It also takes a comparative look, drawing on print media texts from other countries, namely the United States, United Kingdom, New Zealand, and Canada. It employs an innovative combination of large-scale corpus-assisted analysis and close qualitative analysis to identify and explore representations of teachers in the print media, how they are constructed and how these constructions have changed and shifted over the past twenty five years.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".