Effects of perceived scarcity on <scp>COVID</scp>‐19 consumer stimulus spending: The roles of ontological insecurity and mutability in predicting prosocial outcomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In 2021, the United States government provided a third economic impact payment (EIP) for those designated as experiencing greater need due to the COVID‐19 pandemic. With a particular focus on scarcity and ontological insecurity, we collected time‐separated data prior to, and following, the third EIP to examine how these variables shape consumer allocation of stimulus funds. We find that scarcity is positively associated with feelings of ontological insecurity, which, interestingly, correlates to a greater allocation of stimulus funds toward charitable giving. We further find evidence that mutability moderates the relationship between ontological insecurity and allocations to charitable giving. In other words, it is those who feel most insecure, but perceive that their resource situation is within their control, who allocated more to charity giving. We discuss the implications of these findings for theory, policy‐makers, and the transformative consumer research (TCR) movement.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it