MétaCan
Menu
Back to cohort
Record W4413283683 · doi:10.1080/0267257x.2025.2547379

Mental illness as consumer vulnerability: ambivalent attachment to the college campus

2025· article· en· W4413283683 on OpenAlexaff
Carly Drake, Mehdi Mourali, Kelly Pender

Bibliographic record

VenueJournal of Marketing Management · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsKingston Health Sciences CentreUniversity of Calgary
Fundersnot available
KeywordsAmbivalenceVulnerability (computing)PsychologyMental illnessSocial psychologySociologyMarketingBusinessAdvertisingMental healthPsychotherapistComputer security

Abstract

fetched live from OpenAlex

In this study, we examine how consumers understand and negotiate mental illness in a marketplace that does not always offer empathy. We employ theory on place attachment and spatial vulnerability to discover how person-place bonds form (or not) when consumers’ agency and power may be restricted in complex, protracted ways. We situate our research in the context of the college campus, mobilising data from semi-structured interviews with 25 college students diagnosed with anxiety and/or depression. Students’ narratives are enriched with their hand-drawn maps of the campus and surrounding community, a process called counter-mapping. Data were interpreted using hermeneutics. Findings show a form of ambivalent place attachment that develops through consumer perceptions of physical, social, and symbolic (in)security. Students’ attempts to regain power within and control over their environment takes the form of often-maladaptive coping mechanisms that threaten students’ personal and academic wellbeing.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.009
Scholarly communication0.0050.004
Open science0.0000.007
Research integrity0.0010.003
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 head0.022
GPT teacher head0.401
Teacher spread0.379 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Marketing ManagementSame topicHomelessness and Social IssuesFrench-language works237,207