Skip to content

Error-type profiling

Research Method · All research methods
Evidence · 1 claim (1 for) · 1 study (1 causal), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

Error-type profiling is the analytic lens the article introduces to judge fairness interventions by how they redistribute false positives and false negatives across groups, rather than only by whether fairness metrics converge. The article introduces it as "a lens that translates fairness metrics into the terms advisors actually encounter: which students appear on caseloads and which are never seen." With predicted-successful as the positive class, a false negative is a successful student predicted at-risk who occupies a scarce advising slot and risks stigmatization, while a false positive is a struggling student predicted successful who never appears on any advisor's caseload.

Accounts

  • Error-type profiling: translating fairness metrics into the errors advisors and students encounter: Error-type profiling is the analytic lens the article introduces to judge fairness interventions by how they redistribute false positives and false negatives across groups, rather than only by whether fairness metrics converge. The article introduces it as "a lens that translates fairness metrics into the terms advisors actually encounter: which students appear on caseloads and which are never seen." With predicted-successful as the positive class, a false negative is a successful student predicted at-risk who occupies a scarce advising slot and risks stigmatization, while a false positive is a struggling student predicted successful who never appears on any advisor's caseload. (McConvey et al. (2026))
  • Iteration branch of the taxonomy: seven categories of loop difficulties: The iteration branch classifies difficulties with loops into seven categories: the repeating nature of iteration statements, interaction with code outside the loop, order of execution of loop parts, state (including control-variable difficulties), difficulties with the loop condition, nesting, and break and continue. Examples include the "loop is if" belief and thinking nested loops execute simultaneously. The branch draws on both cited literature and the authors' own interview and test data. (Dimitri Eckert et al. (2026))

Claims

-

Key Sources

  • McConvey, K., Zhai, A., Li, R., & Guha, S. (2026). Fairness Theatre: Evaluating Post-Hoc Fairness Interventions in Vendor-Controlled Early Warning Systems. arXiv. https://arxiv.org/abs/2609.38552. doi:10.48550/arxiv.2609.38552
  • Dimitri Eckert and Christian Kautz. (2026). How Students (Mis)understand Conditionals and Loops – A Taxonomy. arXiv preprint. https://arxiv.org/abs/2605.26966v1
Page metadata
Field Value
type research-method
id error-type-profiling
title Error-type profiling
description Error-type profiling is the analytic lens the article introduces to judge fairness interventions by how they redistribute false positives and false negatives across groups, rather than only by whether fairness metrics converge.
status review
generated by process:settle-candidates on 2026-10-10
trust unverified — no one has confirmed this page's content

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