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Record W3114115862

Exploring Queer Joy: The Importance of Positive LGBTQ+ Narratives

2020· article· en· W3114115862 on OpenAlexaffabout
Janine Heber

Bibliographic record

VenueStudent Research Proceedings · 2020
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsMacEwan University
Fundersnot available
KeywordsQueerHappinessNarrativeGender studiesLesbianOstracismAestheticsSociologyPsychologyMedia studiesSocial psychologyArtLiterature
DOInot available

Abstract

fetched live from OpenAlex

Media is a powerful tool for socializing society about norms. Media portrayals of LGBTQ+ narratives often reinforce heteronormative ideals in society. Lack of representation or narratives that exploit the trauma of LGBTQ+ characters can lead to associations of queerness with negative outcomes and unhappiness. However, LGBTQ+ narratives that focus on the joy and happiness between characters can serve as a catalyst for acceptance. As such, it is important to celebrate and highlight series like Schitt’s Creek which intentionally show the tenderness, happiness, acceptance, and love of LGBTQ+ characters. The centre of the hoop is the hand embroidered image from the show's billboard. In an interview, Daniel Levy, the co-creator of Schitt’s Creek, shared that he wanted to do something bold for the final season and that his younger self would never have dreamed of seeing a billboard with two men kissing. Many fans have taken photos in front of the billboard to share their acceptance and celebration of queer love. When young sunflowers grow, they turn towards the direction of the sunlight during the day and reverse course at dawn so they are ready for morning. A study by Harmer in 2016 found that restricted sunflowers that were unable to turn were smaller in size and had fewer petals. In the same way, lack of positive LGBTQ+ narratives negatively impact the lives of LGBTQ+ people. Here, the border of sunflowers represents a collective turning towards LGBTQ+ joy, health, and happiness. When we celebrate and support positive and healthy LGBTQ+ media representations, like the sunflowers in sunlight, we can all flourish and grow. Presented in absentia on April 27, 2020 at Student Research Day at MacEwan University in Edmonton, Alberta. (Conference cancelled) Faculty Mentor: Katie Biittner Department: Gender Studies

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 score0.260
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.405
GPT teacher head0.502
Teacher spread0.097 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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