In/visible families : exploring the experiences of lesbian, gay, bisexual, queer, trans-identified, and two-spirited parents in Northern Ontario school communities / by Natalie Rowlandson.
Bibliographic record
Abstract
The purpose of this study was to learn about the nature of interactions between Lesbian, Gay, Bisexual, Queer, Trans-identified, and Two-Spirited (LGBQTT) parents and their children?s teachers and school principals. A case study and narrative inquiry methodology was used to examine the research questions in this study. Semi-structured interviews were conducted to capture the experiences o f six parents in Northern Ontario. This method of study allowed for each participant to tell their own story about their thoughts, feelings, and perceptions about being an LGBQTT parent in a school community. Five common themes were identified during data \nanalysis. These themes were: (1) coming out at school; (2) impact of disclosure on their children; (3) acceptance and validation; (4) lack of representation of non-normative families; and (5) high parental involvement in their children?s schools. The participants in this study emphasized the \nimportance of full disclosure of family structure in school. They felt accepted and validated by school staff, but were acutely aware that homophobia and heterosexism nevertheless exists in school communities. The thesis concludes with recommendations for teachers, principals, and LGBQTT parents, as well as ideas for future research.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".