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GRE Verbal · Question of the Day

GRE Verbal Question of the Day

A fresh daily question to build accuracy, reinforce recall, and turn practice into a steady habit.
Thursday, October 8, 2026

Read the passage and answer the question.

In recent years, some legal scholars have advocated for "algorithmic sentencing" tools that estimate recidivism risk to guide judges. Supporters argue that statistical models can reduce idiosyncratic disparities by making decisions more consistent. Yet the apparent objectivity of such tools can be misleading: the models are trained on historical data shaped by policing patterns, charging practices, and plea bargaining, all of which embed prior inequities. Additionally, the choice of outcome variables—rearrest, reconviction, or violation—quietly encodes normative judgments about what counts as reoffending. Risk scores may help structure discretion, but they can also launder contested values through technical vocabulary, making policy choices harder to contest in public terms.

The passage conveys an attitude that is primarily…​

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Question of the Day

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Read the passage and answer the question.

In recent years, some legal scholars have advocated for "algorithmic sentencing" tools that estimate recidivism risk to guide judges. Supporters argue that statistical models can reduce idiosyncratic disparities by making decisions more consistent. Yet the apparent objectivity of such tools can be misleading: the models are trained on historical data shaped by policing patterns, charging practices, and plea bargaining, all of which embed prior inequities. Additionally, the choice of outcome variables—rearrest, reconviction, or violation—quietly encodes normative judgments about what counts as reoffending. Risk scores may help structure discretion, but they can also launder contested values through technical vocabulary, making policy choices harder to contest in public terms.

The passage conveys an attitude that is primarily…​

  1. Cautiously critical, warning that technical tools may obscure normative and historical biases (correct answer)
  2. Celebratory, portraying algorithmic sentencing as a straightforward fix for injustice
  3. Neutral and purely explanatory, avoiding any evaluative stance on the tools
  4. Furious denunciation, accusing judges of intentionally using tools to oppress defendants
  5. Dismissive contrarianism, denying that disparities in sentencing exist

Explanation: This question tests the reader's ability to identify the author's tone toward algorithmic sentencing tools. Tone is conveyed through diction and emphasis, critiquing misleading objectivity while noting potential structure. The passage concedes models can 'reduce idiosyncratic disparities' but warns they embed 'prior inequities' and encode normative judgments. It further notes they can 'launder contested values' through technical means. Therefore, choice A reflects this cautiously critical warning about biases. Choice B is a celebratory distractor, portraying a straightforward fix, ignoring the author's emphasis on historical data issues. Choice E fails by dismissively denying disparities, contrary to the passage's recognition of them.