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Record W4386900170 · doi:10.1177/20563051231196868

Curating Hope: The Aspirational Self and Social Engagement in Early-Onset Cancer Communities on Social Media

2023· article· en· W4386900170 on OpenAlex
Jaigris Hodson, Victoria O’Meara

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

VenueSocial Media + Society · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicMedia, Religion, Digital Communication
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsAffordanceSocial mediaContext (archaeology)PsychologyPhenomenology (philosophy)Social psychologySociologyCognitive psychologyWorld Wide WebEpistemology

Abstract

fetched live from OpenAlex

Early-onset cancer patients, survivors and caregivers have unique needs in comparison to their older counterparts. As a result, they often turn to social media to find others with similar experiences. This study employs hermeneutic phenomenology to understand the unique needs of early-onset cancer patients and caregivers as they engage with communities related to their illness across different social media platforms. Drawing from such theories as uses and gratifications, context collapse, and aspirational self-presentation, this study shows how people engaging with social media communities related to early-onset cancer employ “affordances-in-practice,” choosing what to post based both on the technical affordances of each platform, and on the audience they imagine to be on each platform. We find that in addition to seeking information and social support, participants in early-onset cancer communities use social media to seek hope. This finding suggests a nuanced reconsideration of the existing dichotomy between online authenticity and the aspirational self on social media platforms like Instagram.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.997

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 studies0.0040.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.145
GPT teacher head0.310
Teacher spread0.166 · 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