YOU BETTER WERK: Disrupting and Queering Professionalism in Early Childhood Education and Care
Bibliographic record
Abstract
[Introduction}: " “I am a professional,” and “I came to werq.” (Shangela, 2012). This message from Shangela’s 2012 song “Werqin’ Girl” signifies the importance of hard work to attain “professional” status as a drag performer. It also relates to the mainstream success that drag culture has enjoyed in recent years, which can be credited to the global success of RuPaul’s Drag Race. Werq or “werk” is a term that describes the passionate labour that goes into marketing a drag persona and making a career out of it. Historically, it aims to call out heteronormativity and challenge dominant cultural norms (Lovelock, 2019). In a sense, the hard werk of drag queens and kings disturbs the cultural and societal norm of what constitutes “professional behaviour” or “professionalism.” This normalcy in what constitutes “professionalism” also exists in the field of early childhood education. For example, the Code of Ethics and Standard of Practice, a document that guides professionalism for early childhood educators in Ontario, indicates that an educator that exhibits professionalism is “knowledgeable” in practice that is “caring and responsive on children’s development, learning, self-regulation, identity and well-being” (College of Early Childhood Educators, 2017, p. 8)."
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.033 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".