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Record W4416324136 · doi:10.1177/10616934251383656

The Influence of a Cause-Related Marketing Initiative on Attitudes Toward an Intercollegiate Athletic Department

2025· article· en· W4416324136 on OpenAlex
Erica Thompson, Michael L. Clemons, Jeffrey T. Ward, Chris Greenwell

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

VenueSport Marketing Quarterly · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsRunning Injury Clinic
Fundersnot available
KeywordsRespondentPresentation (obstetrics)Sports marketingPerceptionValue (mathematics)Marketing communication

Abstract

fetched live from OpenAlex

Sport organizations often use cause-related marketing (CRM) initiatives to enhance their image. However, CRM initiatives often fall short of intended objectives. Utilizing signaling theory, this study examines how a CRM initiative may influence college students’ attitudes toward the athletic department. Respondents were shown a social media message promoting a mental health-related CRM initiative sponsored by an intercollegiate athletic department, and respondents’ attitudes toward the athletic department were compared pre- and postviewing the message. A repeated-measures analysis of covariance design was utilized to examine if message presentation and/or respondent gender affected the change in attitudes toward the athletic department. Results indicate that CRM initiatives positively impact attitudes toward athletic departments, and female respondents showed a more significant attitude change than male respondents. Findings suggest there is value in athletic departments engaging in CRM initiatives, especially when targeting female consumers.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.020
GPT teacher head0.308
Teacher spread0.288 · 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