Scarcity Captures Attention and Induces Neglect: Eyetracking and Behavoral Evidence
Bibliographic record
Abstract
Scarcity poses challenging demands on the mind that can make escaping scarcity difficult. Using eyetracking and behavioral evidence, we find that scarcity induces an attentional focus, enhancing processing of scarcity-relevant information, while at the same time causing a failure to notice peripheral material, including information that may have proven beneficial in alleviating the scarcity condition. Participants were randomly assigned to a scarcity condition (with a small budget) or a control condition (with a large budget) while ordering a meal from a menu in a lab setting, while their eye gaze was tracked. We found that, compared to controls, participants under financial scarcity looked more at price information but less at the food items, calories and a discount that could alleviate their budget constraint (Experiment 1). In a subsequent memory test, participants under scarcity recalled price information more accurately than control participants (Experiment 2), and likewise those under calorie scarcity recalled calorie information more accurately than controls (Experiment 3). The results were replicated in a larger participant sample, where those under scarcity were less likely to request the discount than control participants (Experiment 4, Experiment 5 as a pre-registered replication). This neglect could be due to limited attention to peripheral information under scarcity (Experiment 6). These results support the notion that scarcity induces an attentional focus on scarcity-relevant information, while causing neglect elsewhere, including of beneficial information that can alleviate the scarcity condition. The findings help explain a range of counter-productive behaviors under scarcity and suggest ways to think about policy design and implementation to better guide attention and prevent neglect.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".