The effect of source reliability and information credibility on judgments of information quality in intelligence analysis
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 The quality of information that informs decisions in expert domains such as law enforcement and national security often requires assessment based on meta-informational attributes such as source reliability and information credibility. Across 2 experiments with intelligence analysts ( n = 74) and nonexperts ( n = 175), participants rated the accuracy, informativeness, trustworthiness, and usefulness of information varying in source reliability and information credibility. The latter 2 attributes were communicated using ratings from the Admiralty Code, an information-evaluation system widely used in the defence and security domain since the 1940s. Ratings of accuracy, informativeness, and likelihood of use were elicited as repeated measures to examine intraindividual reliability. Across experiments, intraindividual reliability was best when levels of source reliability and information credibility were moderately consistent compared to when they were maximally inconsistent (i.e., one low and one high) or maximally consistent (both high or low). As well, trustworthiness ratings depended more on source reliability than on information credibility. Finally, the likelihood of using information was consistently predicted by accuracy ratings and not by judged informativeness or trustworthiness. The current findings offer insights into the ability of experts and novices to reliably use information-evaluation systems for structuring human judgments about intelligence.
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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 | 0.003 | 0.001 |
| 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 | 0.001 |
| 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