MétaCan
Menu
Back to cohort
Record W2109088623 · doi:10.1145/1753846.1753893

Thanatosensitively designed technologies for bereavement support

2010· article· en· W2109088623 on OpenAlexaff
Michael Massimi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAcknowledgementProcess (computing)PopulationPsychologyComputer scienceInternet privacyComputer securityMedicine

Abstract

fetched live from OpenAlex

Computing supports a number of activities across the lifespan, from interactive games for children to smart homes for seniors. However, one part of the lifespan which is often overlooked by application designers is the end of life - a period marked by issues of mortality, dying, and death. My thesis takes up this area as its object of study, and does so specifically by examining the bereaved as a target population. I argue that most modern technologies are not designed with proper acknowledgement of the eventual death of their users, and that this oversight results in a series of circumstances which complicate affairs for bereaved family members. Based on evidence from a survey and interview study, I identify opportunities for technology designers to support bereavement activities through a process called "thanatosensitive design." My thesis seeks to contribute methodological insights for designing for the end of the lifespan, a novel system which connects bereaved individuals together, and account of how this system mediates social support.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: Other design
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0020.005
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 head0.019
GPT teacher head0.283
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations16
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicInnovative Human-Technology InteractionFrench-language works237,207