The development and the use of gender-affirming online resources and games for gender-independent, intersex, non-binary, and transgender (GIaNT) children and youth: A scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: The objective of this scoping review protocol is to review what has been reported on the development and the use of gender-affirming online resources and games for gender-independent, intersex, non-binary, and transgender (GIaNT) youth (aged 9-26). INTRODUCTION: GIaNT youth and their specialized health care needs are mostly exempt from curriculums. There is limited information on the specific online sources available for GIaNT children and youth. INCLUSION CRITERIA: The inclusion criteria are sources that include GIaNT children and youth and focus on online spaces and games for the identified population. METHODS: The Joanna Briggs Institute (JBI) method for scoping reviews has guided the development of this protocol. Databases to be searched include CINAHL, Cochrane, Epistemonikos, ERIC, Gender Studies Database, GenderWatch, LGBTQ+ Source, ProQuest, PyscInfo, and Scopus. Unpublished studies and gray literature searches will be undertaken in ProQuest thesis and dissertation and a limited number of relevant websites. No limit on date or region will be applied. Records will be screened and extracted by two independent reviewers. Results will be presented as tables with accompanying narrative summary. CONCLUSION: This scoping review protocol will guide the review and mapping of literature on available sources for online spaces and games for GIaNT children and youth.
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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 | 0.146 | 0.148 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.016 | 0.009 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.057 | 0.012 |
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".