Claims

Email-detection confidence judgments show good calibration but poor resolution, with aggregate overconfidence of 18%

Claim · All claims
Evidence · 1 study · causal r2 · q3
Currency · newest study 2019 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2022: tool and model accuracy changes quickly

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q3 i? Across two experiments, participants' mean confidence (85%) exceeded mean accuracy (67%), and calibration was generally good while resolution was very poor. → Casey Inez Canfield & Baruch Fischhoff & Alex Davis 2019

Evidence

Casey Inez Canfield & Baruch Fischhoff & Alex Davis 2019

Casey Inez Canfield & Baruch Fischhoff & Alex Davis. (2019). Better beware: comparing metacognition for phishing and legitimate emails. Metacognition and Learning. https://doi.org/10.1007/s11409-019-09197-5

q3 · i? · causal · r2

Pooled analysis of two experiments (152 mTurk and 98 SBO participants; 250 total) scoring detection judgments with the Brier decomposition. The article reports "aggregate overconfidence of 18%" and states calibration was generally good while "resolution was very poor."

"Across all questions and individuals, mean confidence was 85% ( SD =8 % ) . Mean accuracy was much lower at 67% ( SD = 11%), making for aggregate overconfidence of 18%"

Discussion

Page metadata
Field Value
type claim
id phishing-metacognition-good-calibration-poor-resolution
title Email-detection confidence judgments show good calibration but poor resolution, with aggregate overconfidence of 18%
description Email-detection confidence judgments show good calibration but poor resolution, with aggregate overconfidence of 18%
status review
evidence_strength moderate
newest_evidence 2019
recheck_by 2022
generated by process:wiki-ingest on 2026-10-18
trust unverified — no one has confirmed this page's content
sources 1 — casey-inez-canfield-baruch-fischhoff-alex-davis-2019

Frontmatter is the page's machine-readable record — see the Schema & Guide.