Supporting the development of sexuality in early childhood: The rationales and barriers to sexuality education in early learning settings
Bibliographic record
Abstract
Learning about sexuality is an important part of development in early childhood but is not formally considered in early learning settings. This makes sexuality education for young children both rare and inconsistent across early learning settings. The purpose of this paper is to provide a unique contribution and inform the state of sexuality education in early learning settings in Canada, which is currently an understudied area. We describe the Canadian context of sexuality education in early learning settings and examine its presence in provincial and territorial early learning frameworks. We advocate for the inclusion of sexuality education in early learning settings because it can support children’s development and construction of sexuality, is a critical factor in providing children with personal safety skills and a part of child sexual abuse prevention work, and also sets the foundation for equity and social justice in teaching children about diversity as a norm. We discuss the barriers which act to exclude sexuality education in early learning settings including a lack of curriculum and policy to guide early learning professionals in addressing and supporting this domain, fear of parent reactions, and theoretical constructions of childhood innocence. We conclude with practice and policy recommendations to move the field forward.
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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 | 0.036 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.051 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".