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Record W4383682673 · doi:10.1145/3563657.3596020

PhotoClock: Reliving Memories in Digital Photos as the Clock Ticks in the Present Moment

2023· article· en· W4383682673 on OpenAlexafffund
Amy Yo Sue Chen, William Odom, Sol Kang, Carman Neustaedter

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsTemporalitySlownessComputer scienceMetadataContemplationDigital clockDigital mediaEphemeral keyMultimediaVisual artsWorld Wide WebArtTelecommunications

Abstract

fetched live from OpenAlex

As digital photos grow exponentially, people need new approaches to engage with their photos over time. We describe our study of PhotoClock, a mobile application that leverages the temporal metadata embedded in digital photos to encourage contemplation of memories bound up in one's photo archive. PhotoClock uses the clock-time of the present moment to re-present one's photos taken around that same time of the day in the past. As time ticks away relentlessly, PhotoClock highlights the ephemeral and ongoing quality of time. We conducted the field study with 12 participants over 8 weeks. Our goals are: (i) to investigate the reflective potential of clock-time as an alternative design approach for supporting memory-oriented photo interaction, and (ii) to explore conceptual propositions related to slowness and temporality. Findings revealed that PhotoClock generated diverse and reflective experiences on participants’ life stories. We conclude with implications and opportunities for future HCI and design research.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.020
GPT teacher head0.287
Teacher spread0.267 · 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.

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

Citations9
Published2023
Admission routes2
Has abstractyes

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