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Record W4225124634 · doi:10.1145/3491102.3517580

Strategies for Fostering a Genuine Feeling of Connection in Technologically Mediated Systems

2022· article· en· W4225124634 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

VenueCHI Conference on Human Factors in Computing Systems · 2022
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsFeelingConnection (principal bundle)Computer scienceHuman–computer interactionPsychologySocial psychologyEngineering

Abstract

fetched live from OpenAlex

Human connection is essential for our personal well-being and a building block for a well-functioning society. There is a prominent interest in the potential of technology for mediating social connection, with a wealth of systems designed to foster the feeling of connection between strangers, friends, and family. By surveying this design landscape we present a transitional definition of mediated genuine connection and nine design strategies embodied within 50 design artifacts: affective self-disclosure, reflection on unity, shared embodied experience, transcendent emotions, embodied metaphors, interpersonal distance, touch, provocations, and play. In addition to drawing on design practice-based knowledge we also identify underlying psychological theories that can inform these strategies. We discuss design considerations pertaining to sensory modalities, vulnerability–comfort trade-offs, consent, situatedness in context, supporting diverse relationships, reciprocity, attention directedness, pursuing generalized knowledge, and questions of ethics. We hope to inspire and enrich designers’ understanding of the possibilities of technology to better support a mediated genuine feeling of connection.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.215
GPT teacher head0.340
Teacher spread0.125 · 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