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Record W3132710073 · doi:10.1177/1524500421990176

Exploring Mistakes and Failures in Social Marketing: The Inside Story

2021· article· en· W3132710073 on OpenAlex
Julie Cook, Jennifer Lynes, Sarah Fries

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 Marketing Quarterly · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSocial marketingExploratory researchMarketing researchField (mathematics)MarketingPerceptionQualitative researchPublic relationsQualitative marketing researchQuantitative marketing researchPsychologyBusinessSociologyReturn on marketing investmentPolitical science

Abstract

fetched live from OpenAlex

Background: Social marketing successes are relatively well-documented, but mistakes and failures in the field are not. When mistakes and failures are reported, they are usually on an ad hoc basis, as opposed to a systematic gathering of evidence. This paper is the second half of a two-part research study that aims to understand the perceptions of social marketing professionals with regard to mistakes and failures in the field. Focus: This article is related to research and evaluation of the social marketing field. Research Question: What are the perceptions of the social marketing community regarding mistakes and failures in the field? Importance to the field: A greater understanding of mistakes and failures in the social marketing field will assist practitioners to assess their own shortcomings, address causes of mistakes and failures, and improve program outcomes. Method: This research is qualitative and exploratory, with a constructivist, grounded theory methodology. Surveys were completed by 100 social marketing community members. Survey data was analyzed and coded using SPSS software and Microsoft Excel. Results: According to the analyzed survey data, the social marketing community believes that inadequate research, poor strategy development, and mismanagement of stakeholders are the most common mistakes made by social marketers. Further, weak evaluation and monitoring is considered to be the “least well-managed” program element. Poor strategy development, external influences, and poorly designed program and behavioral objectives are considered to be the primary reasons for social marketing program failure. Recommendations for research or practice: Future research may explore the extent to which external influences lead to social marketing program success or failure, particularly in comparison to mistakes made by social marketers. Additionally, practitioners should be aware of and develop strategies to mitigate common mistakes and failures in order to improve program outcomes. Limitations: The 100 social marketing professionals who responded to the survey are not representative of the global social marketing community. Further, responses were based on self-report rather than direct observation, which may make them more susceptible to bias.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.061
GPT teacher head0.239
Teacher spread0.178 · 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