Dense Sentence Sets Induce an Anchor-and-Baseline Strategy in Likert Scale Acceptability Judgments

Research in experimental syntax typically assumes that the five-point Likert scale offers an ordinal probe that maps monotonically onto a latent degree of sentence acceptability. We challenge that assumption by showing that, when the stimulus space is densely populated, speakers repurpose the scale into an anchor-and-baseline device. Two large-N experiments (Russian and Serbo-Croatian; N=237; 120 permutational word-order variants per language) elicited over 28000 sentence acceptability ratings. Plotting Shannon entropy of the response distribution against the mean rating reveals a robust 'entropy arch': uncertainty climbs to a sharp peak at the midpoint and collapses toward both ends. We interpret the arch as the quantitative fingerprint of constraint competition: the scale extremes serve as categorical anchors ('completely acceptable' vs. 'completely unacceptable'), while the center functions as a floating baseline against which speakers register maximally uncertain, cue-balanced configurations for which grammatical, information-structural and frequency-based cues pull in opposite directions. Our findings reframe Likert data as the outcome of dynamic calibration rather than static preference strength and provide a simple diagnostic, entropy profiling, for locating linguistic 'tipping-point' constructions. Beyond sentence acceptability, the approach offers a principled way to map regions of maximal competition in any domain where categorical anchors and graded uncertainty coexist.