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Record W7010138525

Gaming For Growth: Reimagining Counseling for Folks on the Autism Spectrum

2021· other· en· W7010138525 on OpenAlexaboutno aff

Bibliographic record

VenueNational University System Repository (National University System) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNeurotypicalAutismPopulationAgency (philosophy)Mental healthCapstone
DOInot available

Abstract

fetched live from OpenAlex

Autism Spectrum Disorder (ASD) is an extremely common developmental disability, affecting just under 2% of the population in Canada (Public Health Agency of Canada, 2018). This population faces many of the same mental health struggles as neurotypical individuals, often at much higher rates, and yet accessing counseling often comes with a series of additional barriers due to the complexities of life on the Autism spectrum. As such there is a clear need for a deeper examination into the way we offer counseling to this oft-neglected segment of the population, and this capstone will attempt to address that need. In chapter one I will provide an in-depth examination of this problem and explain why the development of ASD-sensitive forms of therapy is necessary. In chapter two I will address the five forms of therapy most used when counseling clients with ASD, identifying their benefits and highlighting their drawbacks. Finally, in chapter three I will outline a new model of counseling for this population based around the popular roleplaying game Dungeons and Dragons.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.765
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.021
GPT teacher head0.216
Teacher spread0.195 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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