Better or different? Self‐differentiating appeals interact with self‐theories to predict volunteer intentions
Bibliographic record
Abstract
Abstract This research explores how charities can harness individuals' desire for self‐enhancement in their advertisements to boost volunteerism. Two studies examine the effects of advertising which promote either horizontal differentiation (appeals to uniqueness, existing skills) or vertical differentiation (appeals to status, skill acquisition) and how these interact with consumers' self‐theories (incremental—belief in changeable attributes through effort, or entity—belief in unchangeable attributes). Study 1 (n = 183, 56% female) shows entity theorists are more inclined to volunteer following horizontally framed appeals, while incremental theorists respond similarly to both types of appeals. Study 2 (n = 107, 58% female) builds on this, revealing that self‐theory influences the type of individuation (horizontal or vertical) sought by individuals, in turn enhancing volunteer intentions. These findings highlight the complex relationship between self‐theory and advertising appeals in motivating volunteerism, offering valuable insights for creating effective charitable ads and understanding volunteer motivations.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".