Targeting Consumers Who Care about Future Generations
Bibliographic record
Abstract
ABSTRACT Generativity, as an adult's preoccupation with the well‐being of future generations, is a well‐studied concept in the social psychology literature. However, to this day, little is known about this concept within a consumer context. This article presents two studies that aimed to better understand the attitudes and behaviors of generative consumers. A first study was conducted to develop a more appropriate measure of generativity for consumer situations. It produced a two‐factor consumer generativity scale of six items, one factor of which measures the motivation for symbolic immortality (agentic generativity) whereas the other factor measures the motivation to be useful (communal generativity). The second study showed the predictive validity of the new scale. Highly generative consumers have more favorable attitudes toward ads and products that are generatively positioned. Generative consumers intend to buy products positioned as generative. In addition, the second study presents some sociodemographic characteristics of generative consumers. This research presents a valid and parsimonious scale of consumer generativity, and demonstrates the relevance of using a generative positioning strategy when targeting highly generative consumers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".