A framework to explore lifelong learning: the case of the civic education of civics teachers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study investigates learning about civics and citizenship throughout individuals' lives (lifelong) and across various pedagogical settings (lifewide). A basic hypothesis is that civics teachers, among all social actors, are particularly well positioned for engaging in this type of introspective exercise because they are both familiar with civics and politics and also with teaching and learning processes. The lifelong civic learning of civics teachers was examined in the different settings in which they acquire their knowledge, values, skills and ideological frameworks, and to understand the relative weight of each one in their overall learning process. This study also coincides with the implementation of a new provincial civics course for grade 10 students in Ontario, Canada during the 2000–1 school year. This case study consists of interviews with 15 social studies teachers who have taught the new civics course in Ontario. One of the clearest findings of the study is the powerful influence of the experience of teaching and of early family socialization on the acquisition of civic knowledge, skills and values, and on the development of political beliefs. Civic engagement and political participation were also considered an important source of civic learning, particularly in relation to the acquisition of civic and political skills. This is a finding that deserves further exploration, because our understanding of social movement learning remains limited. The findings suggest the promotion of lifelong citizenship learning entails the creation and nurturing of inclusive democratic spaces that have particularly high civic educational potential.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it