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Record W4403767601 · doi:10.1177/10497323241287453

How Do Men Who Post Publicly on Social Media Author Themselves and Their Experiences of Crohn’s Disease? A Dialogical Analysis of Three Cases

2024· article· en· W4403767601 on OpenAlexaboutno aff
Lucy Prodgers, Brendan Gough, Anna Madill

Bibliographic record

VenueQualitative Health Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsnot available
FundersUniversity of Leeds
KeywordsDialogical selfSocial mediaPsychologySocial psychologyQualitative researchSociologySocial science

Abstract

fetched live from OpenAlex

Despite distinct sex- and gender-related differences in the presentation and manifestation of Crohn's disease (CD), little research to date has considered men's particular experiences. Whilst hegemonic masculine ideals have been reported to negatively impact men's mental and physical health, increasingly research has emphasized that men engage in a diverse range of practices, including those beneficial to health. One such practice is posting about their illness experiences on social media. The interactive nature of posting online means that a dialogical approach, based on a relational epistemology, is particularly useful. This study therefore asked: "How do men who post publicly on social media author themselves and their experiences of CD?" Three participants were recruited, all of whom had a diagnosis of CD, wrote a blog, and posted on other social networking sites (SNSs) about CD. Two resided in Canada and one in the United Kingdom. All were white. For each participant, 2 years of multimodal social media data was downloaded. After screening, in-depth analysis was conducted using a dialogical approach focusing on three key dialogical concepts: genre, chronotope, and forms of authorship. The key findings emphasized the participants' different responses to the lack of predictability caused by CD and the different ways they used social media to gain a greater sense of control over their illness stories and identities, providing important insights into the interaction between masculine identities and illness. Finally, the potential deployment of such methods in future research and within therapeutic contexts was considered.

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 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)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
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 head0.558
GPT teacher head0.572
Teacher spread0.014 · 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 teacher head, 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

Citations2
Published2024
Admission routes1
Has abstractyes

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