Methodological improvements for studying face matching in border control 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
Abstract Border control officers must decide whether passport images match their holders. In previous research on passport verification most participants have been more willing to report nonmatching passports than is likely to occur in practice. We designed an experimental paradigm to increase participants' motivation to avoid these types of errors in passport verification. Participants decided whether passport photographs matched ambient photographs of passport holders. Most passports matched their holders and nonmatching passports were rare. All participants received feedback on their passport verification decisions, and an experimental group also received a time‐consuming consequence if they made an error. Relative to the control condition that only received feedback, consequences were effective in reducing mistaken accusations of nonmatching passports. Consequences also increased the miss rate for nonmatching passports, but the increase in misses over the control condition was not significant. We conclude that consequences can make participants behave more like real border control officers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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