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Record W4408855633 · doi:10.1177/23294906251322892

Communicative Care: How Companies Approach Mental Health CSR on Social Media

2025· article· en· W4408855633 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

VenueBusiness and Professional Communication Quarterly · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsMount Royal University
Fundersnot available
KeywordsMental healthCorporate social responsibilityPsychologySocial mediaPublic relationsBusinessPsychiatryPolitical science

Abstract

fetched live from OpenAlex

This study examines Fortune 500 companies’ mental health-related Facebook posts during Mental Health Awareness Month from a CSR perspective. Analyzing 6,264 posts revealed low engagement (1.84%), with half of the posts aligning with WHO-recommended content areas. Posts spanned all CSR typologies, employing diverse information strategies but limited dialogic communication. Despite low engagement, audiences responded positively, particularly to posts on public health, employee involvement, mental health promotion, and human rights. Hyperlinks, graphics, and multimedia boosted interaction and emotional resonance. Findings deepen understanding of effective health-related CSR communication and offer insights into authentic and empathetic CSR strategies for communication training.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.047
GPT teacher head0.364
Teacher spread0.317 · 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