What’s Love Got to Do with It?: Thinking about Democracy in Early Childhood Curriculum with Hannah Arendt
Bibliographic record
Abstract
This paper explores how Hannah Arendt’s view of education as love (1958) can contribute to refreshed perspectives of democratic education. In recent decades, the task of contemporary early childhood education has gradually moved towards an enhanced focus on individual learning and freedom of choice, closely intertwined with an image of the child as an active participant with rights (e.g., Kjørholt, 2012; Sjöstrand Öhrfelt, 2019). The increased emphasis on subject knowledge, measurable achievements, and competition, mainly driven by a neoliberal agenda, is seen to affect and possibly reduce the role of care and democracy within education (e.g., Brogaard Clausen, 2015; Moss, 2017). Arendt’s views on education as love offer a thought-provoking mirror to the changed landscapes of early childhood education. She was critical of the emancipation of children and claimed that, as newcomers, children need to be protected from the world, as well as the world also needing to be protected from the children. Through a theoretical conversation between Arendt and Joan Tronto’s theory of democratic care (2015), I will argue that interdependency and vulnerability need to be acknowledged within contemporary democratic early childhood education, and that allocation of responsibility continues to be an essential issue within education.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.034 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".