Bibliographic record
Abstract
At the present stage of its development, social marketing, and therefore advertising can be applied to promote merit goods, or to make a society avoid demerit goods and thus to promote society's well being as a whole.This is an anti-tobacco campaign, many ways to encourage people to eat right food, to practice "safe sex" to prevent the spread of AIDS, and to join the ranks of donors.Nowadays successful marketing programs are applied in different organizations.Social marketing is the systematic application of marketing, along with other concepts and techniques, to achieve specific behavioral goals for a social good.The primary aim of social marketing is "social good".Health promotion campaigns in the late 1980s began applying social marketing in practice.A variation of social marketing has emerged as a systematic way to foster more sustainable behavior.Referred to as Community-Based Social Marketing (CBSM) by Canadian environmental psychologist Doug McKenzie-Mohr, CBSM strives to change the behavior of communities to reduce their impact on the environment.Realizing that simply providing information is usually not sufficient to initiate behavior change, CBSM uses tools and findings from social psychology to discover the perceived barriers to behavior change and ways of overcoming these barriers.Social marketing uses the benefits of doing social good to secure and maintain customer engagement.In social marketing the distinguishing feature is therefore its "primary focus on social good, and it is not a secondary outcome.Not all public sector and not for-profit marketing is social marketing.Social marketing applies a "customer oriented" approach and uses the concepts and tools used by commercial marketers in pursuit of social goals like Anti-Smoking-Campaigns or fund raising for NGOs
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".