The One-Word Census: Answer-Choice Conformity Across 44 Language Models

A research study evaluating answer-choice conformity across 105 language models from over twenty laboratories demonstrates pronounced output convergence across open-ended queries. When prompted to select a single word from numerous valid possibilities, models frequently converged on identical selections, with 28 of 96 categories exhibiting an 80 percent or higher concentration on a single answer.

This research reveals that diverse language models from distinct developers exhibit severe monocultural convergence when navigating open-ended solution spaces. Organizations relying on multi-model architectures for decision validation face hidden correlated failure modes and homogenized outputs rather than genuine cognitive diversity.

When prompted to 'pick a word' from broad valid option spaces, 105 language models selected the word 'serendipity' 46 percent of the time.

Forward consideration, not a verified fact.