Book Review: Smyth, J., Angus, L., McInerney, P., & Down, B. (2008). Critically engaged learning: Connecting to young lives
Bibliographic record
Abstract
Critically Engaged Learning: Connecting to Young Lives by John Smyth, Lawrence Angus and Peter McInerney, Barry Down provides revitalization and recharged zeal for educators struggling to reach disengaged youth. Teachers show a remarkable capacity to build productive relationships with students (Smyth et al., 2008). This book celebrates the stories of successful teachers and communities who engage young people in ‘real world’ learning. Though the debate on early school leavers and the enhancement of school arrangements for young learners has been in place for some time (Smythe & McInerney, 2007), this study moves beyond the school context “to examine the institutional and community processes of capacity building that lead to improved learning for students” (p. x). By critically interrogating many of the basic assumptions on which issues of student retention and student engagement are based, this book turns the tide of student disengagement towards ‘a people’s scholarship’ (Featherstone, 1989).
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.048 | 0.051 |
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".