MétaCan
Menu
Back to cohort
Record W4402218346 · doi:10.1111/cars.12484

Friendlessness and loneliness: Cultural frames for making sense of disconnection

2024· article· en· W4402218346 on OpenAlexafffundabout
Laura Eramian, Peter Mallory, Morgan Herbert

Bibliographic record

VenueCanadian Review of Sociology/Revue canadienne de sociologie · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsSt. Francis Xavier UniversityDalhousie University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLonelinessDisconnectionPityLamentShameSocial psychologySociologyPsychologyMeaning (existential)Stigma (botany)AestheticsPolitical scienceLiteratureArtPsychotherapistLaw

Abstract

fetched live from OpenAlex

This article is based on 21 interviews in an Atlantic Canadian city with people who identified as having few or no friends. With all the talk of a modern loneliness epidemic, we might easily assume friendless people are lonely, yet here we take an interpretive approach to analyze how they alternately claim to experience and not experience loneliness. We argue that claims to loneliness or its absence are never merely personal stories or problems of individual health or wellbeing, but are shaped by larger cultural resources and meanings. We found that friendless people both lament and celebrate their disconnection, a duality that we theorize through competing views of the modern self as both autonomous/self-reliant and fundamentally in need of connection and community. We show how our interviewees struggle to find meaning in their disconnection and self-respect in a society where being friendless is open to stigma or pity.

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.996

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.003
Science and technology studies0.0300.069
Scholarly communication0.0120.007
Open science0.0030.014
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.077
GPT teacher head0.379
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 designQualitative
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
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Review of Sociology/Revue canadienne de sociologieSame topicHealth disparities and outcomesFrench-language works237,207