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A QUALITATIVE STUDY OF TRANSGENDER CHILDREN WITH EARLY SOCIAL TRANSITION: PARENT PERSPECTIVES AND CLINICAL IMPLICATIONS

2017· article· en· W2765871452 on OpenAlexaboutno aff
Wallace Wong, S. J. Drake

Bibliographic record

VenuePEOPLE International Journal of Social Sciences · 2017
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsTransgenderTransition (genetics)Qualitative researchDevelopmental psychologyPsychologySociologyGender studiesSocial scienceBiologyGenetics

Abstract

fetched live from OpenAlex

Social transition for young children is a field fraught with conflicting perspectives and limited research. This paper examines experiences of families allowing social transition for young children from the parent’s perspectives and introduces practical ideas from our clinical experiences. Participants were parents of children ages 4 to 9 with gender dysphoria (n=15) in British Columbia, Canada. The children ranged in gender identity and had been under the care of the gender health clinic for a period of one to four years. Participants were self-referred the study and participated in a focus group to describe experiences allowing social transition. Results were transcribed and analyzed using constant comparison qualitative method. Five major themes emerge from this study, including positive changes in the relationship between the child and the parent/family, improvement in social relationship, parent flexibility in the relationship between the child and the parent/family, improvement in social relationship, parent flexibility and preparation for change, and expansion of different gender roles and expressions. Findings indicate social transition for young children results in positive changes in the mood of the child and the child-caregiver relationship as well as improvement in general social relationships. Different clinical implications of permitting early social transition on social development are discussed. 

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.177
GPT teacher head0.573
Teacher spread0.396 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2017
Admission routes1
Has abstractyes

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