MétaCan
Menu
Back to cohort
Record W3099777520

Honouring the voices of 2SLGBTQ+ youth in care within Manitoba

2020· dissertation· en· W3099777520 on OpenAlexaboutno aff
Sylvia Massinon

Bibliographic record

VenueMspace (University of Manitoba) · 2020
Typedissertation
Languageen
FieldSocial Sciences
TopicFeminist Theory and Gender Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGenealogyMedia studiesGender studiesLibrary scienceSociologyHistoryComputer science
DOInot available

Abstract

fetched live from OpenAlex

Two-Spirit, lesbian, gay, bisexual, transgender, queer, intersex, asexual (2SLGBTQ+) youth in care not only have to encounter the challenges that come with being a youth in care, but experience oppression due to colonialism, heterosexism, and cissexism. This Master of Social Work in Indigenous Knowledges thesis centres the voices of five individuals who are a part of the 2SLGBTQ+ community and have had experiences of being in the care of the child welfare system in Manitoba. In the research process there were individual interviews with the five participants, and three of the participants took part in analyzing the summaries of the individual interviews in a group analysis, done by way of talking circle. Overarching themes included oppression at micro, mezzo, and macro levels, and that for some of the Two-Spirit and Indigenous LGBTQ+ participants, cultural identity and gender and/or sexuality, were tied. The major themes that came to light in this process were that being in care had impacts on their sexual and gender identities, impacts on their cultural identities, and that 2SLGBTQ+ youth in care who had the experience of being adopted, and those who did not, had similar experiences. Arriving to the changes that 2SLGBTQ+ youth in care would like to see to better serve 2SLGBTQ+ youth in the care of the child welfare system, there came the major theme of the need for affirmation at the micro, mezzo, and macro levels.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.027
GPT teacher head0.240
Teacher spread0.213 · 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 designQualitative
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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueMspace (University of Manitoba)Same topicFeminist Theory and Gender StudiesFrench-language works237,207