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Record W4402206785 · doi:10.3390/soc14090170

Echoes of Madness: Exploring Disability and Mental Illness in Hellblade: Senua’s Sacrifice

2024· article· en· W4402206785 on OpenAlex
Sina Torabi, Jeff Preston

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocieties · 2024
Typearticle
Languageen
FieldHealth Professions
TopicFilm in Education and Therapy
Canadian institutionsThe King's UniversityWestern University
Fundersnot available
KeywordsSacrificeMental illnessPsychologyPsychoanalysisPsychiatryMental healthPhilosophyTheology

Abstract

fetched live from OpenAlex

Video games are known for many things, but nuanced portrayals of characters with mental illness might not be one of them. This trend, however, has gradually started to shift with games like Hellblade: Senua’s Sacrifice, which aim to convey a genuine experience of mental illness to the player. Through a close reading of different instances in the game, this paper shows how Hellblade complicates the usual sanist ideas seen in most other games by taking an ambiguous stance, using mental illness as a representational tool. Furthermore, it avoids some of the more sensationalist and problematic tropes often employed in such representations, like the supercrip and the Cartesian divide of the body and mind. In order to show this, we have employed Mitchel and Snyder’s concept of narrative prosthesis to demonstrate how the game does not in fact rely on Senua’s disability as an exotic feature of the narrative to hook players in. By combining insights from disability and mad studies, we show how this game is a step in the right direction when it comes to challenging the perceptions of mental illness prevalent in pop culture.

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.

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 score0.171
Threshold uncertainty score0.365

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.098
GPT teacher head0.436
Teacher spread0.338 · 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