Visions and practices of education as transformative tools
Bibliographic record
Abstract
The six articles in this dossier were prepared for a cancelled symposium that was to take place in Salvador, Bahia, in July 2022. The planned symposium was part of a Social Sciences and Humanities Research Council of Canada (SSHRC) Connection Grant , and was to gather members of the Theory and History of Education International Research Group (THEIRG), housed at the Faculty of Education, Queen’s University (https://educ.queensu.ca/their), along with members of the History of Education Research Group (NIEPHE) (https://sites.usp.br/niephe/) and the Thematic Project Education in Borders (https://sites.usp.br/educacaoemfronteiras/) of the University of São Paulo. The papers have in common the analysis of visions of education and educational aims in relation to social conceptions of change, along with a theological, philosophical, or socio-political ethical foundation. The authors do not neglect the agency of the individual as either an individual or a collective self – neither the contextual nuances nor the unexpected implications of the educational process.
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 | 0.025 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.089 |
| Scholarly communication | 0.027 | 0.017 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".