Associations between protestant work ethic and multilevel marketing participation and financial outcomes
Bibliographic record
Abstract
Multilevel marketing (MLM) involvement can adversely affect consumer wellbeing. We examine how individual beliefs about work predict participation and financial losses in MLMs. As MLMs are presented to the marketplace as low-barrier opportunities to start one's own business, we suggest that this may speak directly to people who strongly endorse Protestant work ethic (PWE), making them more inclined toward MLM participation, and financial outcomes associated with that participation. Using a place-based (county level) MLM data set from the Federal Trade Commission (FTC; n = 326,487), and a consumer survey (n = 515), we find evidence that PWE is positively associated with participation in MLMs (studies 1 and 2), and that PWE predicts estimated financial losses among those who lost $1000 or more (study 1) but financial gains in a more general sample of MLM participants (study 2). Implications for research, marketing, and consumer advocacy are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".