Ethics in compulsory education – Human dignity, rights and social justice in five contexts
Bibliographic record
Abstract
What children learn through their ethics and values education in school is of crucial societal relevance and is directed by school curricula. As curricula vary between countries, an international comparison is of interest. The aim of this study was to compare curricula to reveal variations in how matters of social justice were described in curricular texts, with a special focus on class, gender and race. Curricula from five different contexts were compared: Namibia; South Africa; California State, United States of America; Province of Québec, Canada; and Sweden. This provided the study, originating in Sweden, with crucial comparative material from outside Europe. The studied curricula were systematically searched for the importance and significance of the terms ‘poverty/poor’, ‘gender’, ‘equity’, ‘equality’, ‘justice’, ‘race’, ‘racism’, ‘human dignity/rights’, ‘equal value’ and Ubuntu. Methodologically, this represented a qualitative content analysis approach with a research interest in intersectionality, that is, in how matters of class, gender and race intersect. The study showed considerable variation between the curricular formulations from the five contexts. For example, texts from California and Québec emphasised equality as a general matter and less as one of intersectionality, compared to Namibia and South Africa as well as Sweden. In general, human rights were emphasised, but human dignity less so. For future curricular development towards education as a global common good, matters of social justice, including sustainability, need critical monitoring. The aspects of intersectionality such as class, gender and race are thus crucial, as is the inclusion of an integrated, participatory view on students’ ethical competence.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".