Teaching for Civil Society in Finland: A Canadian Perspective on Finnish Educators' Reflections
Bibliographic record
Abstract
This article describes a study that took place in Helsinki, Finland in late 2015. A Canadian education professor conducted individual interviews with Finnish educators: six practicing teachers in Helsinki schools, two education professors at the University of Helsinki, and the advisor to the president of Finland’s teachers’ union. Although all five Nordic countries are known to support the social welfare state, Finland was chosen because it is considered to be the most economically left. The study is an exploration of how Finnish educators consider their role and the role of the school regarding civil society and the commons in Finland. The actual research question for the study was, “How do Finnish educators think about the school’s role in supporting the commons and in fostering social cohesion with immigration?” The nine participants were unanimous in their support of the commons and Finland’s generous social welfare state, apparently the result of a collectivist mentality in Finnish society. However, there appears to be growing social, economic, and political discrimination for immigrants and refugees who look different from White Finns. The six teacher-participants expressed uncertainty around how best to deal with these tensions, and were committed to attempting neutrality in their teaching of these social problems, or perhaps even ignoring them altogether. Despite the small sample set, I believe it represents a cross section of views of educators in contemporary Finland. Recent studies mentioned in the literature review support this position. Some comparisons with similar studies in Canada are briefly mentioned. Keywords: teaching for social justice; comparative education; Finnish education; controversial issues; Nordic social democracy.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.078 | 0.019 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".