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Record W2588171664 · doi:10.1145/2998181.2998200

In Your Eyes

2017· article· en· W2588171664 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsClosenessFeelingPoint (geometry)Computer scienceFace (sociological concept)Mode (computer interface)Connection (principal bundle)Internet privacyPsychologyHuman–computer interactionSocial psychologySociologyEngineeringMathematics

Abstract

fetched live from OpenAlex

Long distance couples face challenges in staying connected and must rely heavily on technology to mediate their relationship. To provide new ways for couples to virtually 'be together,' we explore a futuristic use of video communications technology where it is possible to see through the eyes of a partner at any point in time to more deeply stay connected and share experiences together on a daily basis. We created a technology probe called In Your Eyes that uses a smartphone and Skype in auto-answer mode. Partners can connect to one another at any time without needing to answer a call. Two couples used the probe for one month. One found it beneficial while the other found it intrusive. We explore the reasons behind these experiences and show the benefits and pitfalls of anytime, anywhere streaming for long distance couples. Our study provides new ways of thinking about presence and connection over distance where the ability to connect and the intention to do so-even if not acted upon-can create feelings of closeness for some and overconnection for others.

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.

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)0.000
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 score0.717
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.050
GPT teacher head0.362
Teacher spread0.313 · 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

Quick stats

Citations39
Published2017
Admission routes1
Has abstractyes

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