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7 1/2 and weekend alarm: Designing alarm clocks for the morality of sleep and rest

2019· article· en· W2943175544 on OpenAlexaff
Anne Spaa, Ron Wakkary, Joep Frens, Abigail Durrant, John Vines

Bibliographic record

VenueTU/e Research Portal · 2019
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPunctualityALARMRest (music)Sleep (system call)Object (grammar)PsychologyComputer scienceMoralityApplied psychologyComputer securitySocial psychologyEngineeringArtificial intelligenceMedicineLawPolitical science

Abstract

fetched live from OpenAlex

Although clocks facilitate good time-management, they have been used in ways that are detrimental to wellbeing. For example, alarm clocks are used to force a person to wake before they have had sufficient sleep and the ambient presence of clocks encourages a constant and sometimes unnecessary need for punctuality. In this paper, we discuss two alarm clocks that are designed to respect wellbeing, improving the ethics of user-object and designer-object relationships. ‘71⁄2’ runs for exactly seven-and-a-half hours, regardless of when it was started, allowing a healthy amount of sleep. ‘Weekend Alarm’ hides its clock face over the weekend, when keeping to time may be less important. The clock designs were purposeful but did not always fit with conventional expectations on functionality. We discuss the process of designing these artefacts for the morality of sleep and rest, and how we came to propose the addition of some unconventional functions to their conventional designs. To inform our reflection on our design approach, we evaluated the devices with two types of participants: two temporary owners, who experienced discomfort but were able to cope with 71⁄2 during the three-week trial, and six design experts who provided critical reviews of both designs.

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)0.011
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.004
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.093
GPT teacher head0.394
Teacher spread0.302 · 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 designSimulation or modeling
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

Citations4
Published2019
Admission routes1
Has abstractyes

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