Financing social marketing programs through sponsorship: implications for evaluation
Bibliographic record
Abstract
Purpose – The purpose of this paper is to report on research designed to assess the impact of sponsorship financing of social marketing initiatives on the evaluation of those social marketing programs. Design/methodology/approach – The research utilizes an in-depth, multi-method case study of the Canadian Mental Health Association Calgary Region (CMHA-CR) who carried out a social marketing campaign concerning mental health behaviors that was largely financed by sponsors. Findings – The sponsorship of the CMHA-CR social marketing program was complex with a total of 15 stakeholders involved as sponsors, partners and grantors. The research reveals that while there is considerable sharing of objectives among the stakeholders in this sponsorship, not all objectives are shared between sponsors and sponsees, and not all objectives are shared between the public and private sector sponsors of the program. Practical implications – The research showed that because sponsors and sponsees share in many of the objectives of the social marketing campaign, the evaluation of the social marketing campaign, particularly its ability to achieve the social marketing-specific objectives, is of interest to all the stakeholder parties, and effective social marketing evaluation must also incorporate evaluation of the non-shared objectives of all sponsorship stakeholders. Originality/value – Increasing social needs, accompanied by reduced government funding and increased competition amongst not-for-profit (NFP) organizations for that funding, are driving NFPs to seek innovative approaches to financing their social programs. The research reports initial findings critical in this environment, as well as raises issues and questions related to future research.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".