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Record W4409894582 · doi:10.14195/2182-8830_11-1_5

What the Body Remembers

2025· article· pt· W4409894582 on OpenAlexaff
Jolene Armstrong, Monique Tschofen, Izabella Pruska-Oldenhof, Kari Maaren, Angela Joose

Bibliographic record

VenueMatlit Revista do Programa de Doutoramento em Materialidades da Literatura · 2025
Typearticle
Languagept
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsCanadian Respiratory Research NetworkToronto Metropolitan UniversityAthabasca University
Fundersnot available
KeywordsPhilosophyEpistemology

Abstract

fetched live from OpenAlex

O nosso artigo discute uma peça de realidade virtual projetada para a Quest 2, Memory Eternal: Book of Mourning, que esteve em exibição no ELO Media Arts Festival. O nosso trabalho, batizado com o nome da oração ortodoxa ucraniana pelos mortos, mergulha os espectadores num espaço de lembrança. A peça reflete sobre o luto a dois níveis — pessoal e coletivo — abordando temas como guerra, pandemia e família. O artigo e o trabalho submetido estão alinhados com os temas da ELO 2023, tendo em conta o papel da literatura na mudança social e perguntando, na esteira de crises globais sobrepostas, o que queremos lembrar e como? Fazemos uma breve tour pelo projeto com a sua paisagem onírica de ruínas medievais povoadas por dez peças distintas de literatura eletrónica que meditam sobre o luto, a dor e o despertar para novos futuros. Discutiremos os métodos colaborativos que utilizamos para criar este trabalho, o qual é fundamentado na ética do cuidado e explicaremos como eles se tornam parte do sentido mais amplo deste trabalho. Finalmente, baseamo-nos em estudos de memória para averiguar de que forma os temas de Memory Eternal servem como uma resposta à crise, uma salvaguarda face à perda e uma promessa de manter a memória viva.

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), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.7230.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.344
Teacher spread0.323 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueMatlit Revista do Programa de Doutoramento em Materialidades da LiteraturaSame topicGrief, Bereavement, and Mental HealthFrench-language works237,207