When Care Becomes Cruel: A Phenomenological Perspective on Educators’ Struggles Amidst Underfunding in Public Education
Bibliographic record
Abstract
Drawing on our empirical study engaging focus groups of highly experienced educators and stakeholders (n = 12) in Ontario, Canada, we examine the cruel refiguration of educational worker care under neoliberalism in public education. Austerity policies have degraded conditions in the schools such that educators are unable to fulfill their attachments to education as a public good. In addition, the neoliberal individualization of responsibility asks workers to address worsening conditions as individuals, collapsing structures of solidarity. In this paper, we explore the phenomenological aspects of how neoliberal individualism structures educator moods, examining educators’ affective interplays of grief, rage, despair, determination, and exhaustion as they struggle to independently uphold or repair a system under duress. We argue that neoliberal conceptions of care are insufficient—and indeed Sisyphean—as singular efforts cannot address the current widespread systemic problems. Instead, we suggest educational workers should disavow individualism, refusing to bear personal responsibility for systemic issues, and should instead seek broader, collective organization against further neoliberal education reforms.
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.033 | 0.072 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.005 | 0.011 |
| 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".