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Record W2096815604 · doi:10.1145/2389176.2389192

Eating alone, together

2012· article· en· W2096815604 on OpenAlexaff
Catherine Grevet, Anthony Tang, Elizabeth D. Mynatt

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSocial connectednessLonelinessFeelingMeaning (existential)PsychologySocial psychologySocial relationshipComputer scienceInternet privacyPsychotherapist

Abstract

fetched live from OpenAlex

Eating with others, or commensality, is an enjoyable activity that serves many important social functions; however, many individuals eat meals alone due to life circumstances, meaning that they miss out on these social benefits. We developed and deployed a simple technology probe providing social awareness around mealtimes to explore how social systems might help alleviate the loneliness of solitary dining. Our findings suggest that these systems can convey a sense of connectedness around a meal; further, our analysis revealed three themes relevant to systems of this type: that contextually-located peripheral awareness engenders connectedness; that such tools can foster a feeling of shared social presence, and that they can be a catalyst for other forms of communication around the meal. These findings suggest that "remote commensality" is not only possible, but that it may take on forms entirely different to that which we are accustomed.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.004

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 head0.027
GPT teacher head0.288
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations47
Published2012
Admission routes1
Has abstractyes

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