Bibliographic record
Abstract
This study examines how social mobility beliefs (SMBs)—consumers’ perceptions of fairness and opportunity for advancement within loyalty programs—influence their willingness to redeem points or miles for carbon offset initiatives. Drawing on Equity Theory, we propose that high SMBs foster perceived fairness, which in turn motivates prosocial behavior. Across four experiments, we demonstrate that members who view loyalty programs as equitable and navigable are more likely to participate in carbon offsetting. Study 1 shows a positive correlation between SMBs and offset participation. Study 2 experimentally manipulates SMBs and confirms their causal influence. Study 3 establishes fairness as the underlying mechanism, ruling out perceived ease of earning loyalty points as an alternative explanation. Study 4 rules out the role of positive emotions as an alternative mechanism. These findings extend SMBs research into consumer contexts and illustrate how psychological justice perceptions within loyalty programs can promote sustainability-oriented actions. Practically, the results offer actionable strategies for designing loyalty programs that align member engagement with corporate social responsibility goals.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".