Gender, Race, and Precarity: Theorizing the Parallels Between Early Childhood Educators and Sessional Faculty in Ontario
Bibliographic record
Abstract
This paper critically examines the parallels of devaluation encountered by early childhood educators and sessional faculty members in Ontario as reflective praxis. The three authors’ experiences are diverse and include a tenured professor and two sessional faculty members, both ofwhom have worked in the field of Early Childhood Education and Care (ECEC). The narratives of the authors inform the concerning trend of precarity and devaluation embedded within two polarizing spectrums of the Ontario educational landscape: Post-Secondary Education (PSE) and ECEC. Although these aforementioned areas of education rarely intersect, the authors centre them on the frontline of the neoliberal assault on education transpiring in Ontario today. The three authors self-identify as female settlers; two have doctoral degrees; one has an MA and is an early childhood educator (ECE). One author self-identifies as a racialized and white-coded cis-gendered woman, and two selfidentify as white, cis-gendered women. All of the authors have worked in Ontario’s post-secondary landscape, one as sessional faculty member and then a tenured professor, and two as sessional faculty members. The paper will problematize the neoliberal assault on higher education and ECEC through a Feminist Political Economy (FPE) conceptual framework in order to draw on the multifaceted ways femAtlantis Journal Issue 40.1 /2019 46 inized discourses devalue the work of ECEs and perpetuate the overrepresentation of women, particularly racialized women in precarious faculty positions.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.045 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".