A critical examination of the evidence for sensitivity loss in modern vigilance tasks.
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
It is well known that when human observers must monitor for rare but critical events, probability of detection tends to wane over time, a phenomenon known as the "vigilance decrement." Over 60 years of empirical study on this topic has culminated in the general consensus that performance suffers due to a loss in observers' ability to distinguish signal from noise (a loss in sensitivity) provided that the task loads memory and stimuli are presented at a relatively high rate. We challenge this assertion on 2 fronts: First, we contend on a theoretical level that the metrics employed to measure observer sensitivity in modern vigilance tasks (derived from signal detection theory) are inappropriate and largely uninterpretable. This contention is supported by an evaluation of recent empirical work in the vigilance domain. Second, we present the results of an experiment that demonstrates that shifts in response bias (the observer's "willingness to respond") over time can masquerade as a loss in sensitivity. Consequently, the basic underlying cause of the vigilance decrement is actually unclear, and may simply reflect a shift in response criterion rather than sensitivity. The theoretical, as well as practical implications of these conclusions are discussed with respect to sustained attention in general, and vigilance in particular.
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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 | 0.006 |
| 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 | 0.000 |
| 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