Legitimacy and sincerity as leveraging factors in social sponsorship: an experimental investigation
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.
Bibliographic record
Abstract
The research presented in this manuscript examines how social sponsorship can be made more commercially effective. To this end, the effects of two leveraging factors are explored by means of an experiment: the extent to which the social sponsorship is seen by consumers as legitimate, and that to which the sponsor is perceived as sincere. The results show that these two factors have a positive and statistically significant impact on consumers’ intentions to purchase the sponsor’s products. In addition, they show that the sponsor’s perceived sincerity increases when the sponsorship is combined with philanthropic investments, either in sequence (i.e. philanthropy followed by sponsorship) or simultaneously, and that the legitimacy of a sponsorship is enhanced when the cause and its sponsor are congruent. These results are discussed in the context of the literature on social sponsorship, and managerial implications for firms that contemplate using social sponsorship as a marketing communication strategy are derived.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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 it