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Record W2372884022

Remember you will [not] die: Mortality versus immortality in a world of patterns and randomness

2015· dissertation· en· W2372884022 on OpenAlexaboutno aff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2015
Typedissertation
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)ImmortalityArgument (complex analysis)Social mediaCritical designSociologyAestheticsMedia studiesArtSocial scienceHistoryWorld Wide WebComputer scienceLiterature
DOInot available

Abstract

fetched live from OpenAlex

This project seeks to explore our perception of death, mortality, mourning processes and death-related rituals within the online world. I specifically look at the Social Network site Facebook as a case study. I argue that new media - such as digital technology like the Internet - is transforming the way we see ourselves and the world, affecting our perception of death and death-related aspects, yet not replacing offline practices. My exploration takes Katherine Hayles’ notion of pattern/randomness as the key theoretical axis and lens of my research.
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\nI strengthen my argument by creating a fictional future scenario situated ten years from now in a Western developed cultural context (i.e. Toronto), where trends of online practices are exaggerated. My studio work, in this scenario, are mourning pieces. It takes the form of wearable technology products that convey Facebook data of a deceased user, and are meant to be used by the bereaved. However, I have created these products from a critical design perspective, wherein products work as commentary, provocation to the public and a way to open up discussion on the topic.
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\nThis thesis project is interdisciplinary in content and form, looking at and exploring fields such as critical theory, philosophy, social science, critical design, various design practices and advertising.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.002
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 head0.133
GPT teacher head0.422
Teacher spread0.288 · 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 designTheoretical or conceptual
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueOCAD University Open Research Repository (OCAD University)Same topicGrief, Bereavement, and Mental HealthFrench-language works237,207