Accounting for the Findings

The foregoing discussion sought to engage the paternalistic vision hypothesis on its own terms, taking the relevant empirical research at face value and identifying theoretical and nonexperimental difficulties facing the supporting theory. If these arguments have succeeded, then the dozens of studies reviewed thus far cannot be explained by paternalistic vision. What, then, accounts for them? This section offers a positive account of the findings typically cited in favor of the paternalistic vision hypothesis: Such effects actually reflect systematic biases in judgment rather than in perception.

Several empirical case studies will fuel this alternative account; however, it must first be acknowledged that a number of prominent findings reviewed earlier—including effects of backpacks, heavy balls, and tools on distance estimates—have not been replicable in other research laboratories. One such study sought to further investigate tool-use effects (Witt et al., 2005) with a new condition and task but instead failed to find the original effect of baton-holding on distance estimates (de Grave et al., 2011). Another examined whether size judgments and triangulated walking measures would corroborate backpack-induced compressions in verbal distance estimates (Proffitt et al., 2003) but instead found no distance-compression effects for any measure (including verbal estimates; Hutchison & Loomis, 2006a, 2006b; Proffitt, Stefanucci, Banton, & Epstein, 2006a, 2006b). Others have scrutinized more recent “indirect” findings (Ontiveros, Mejia, Liebenson, Lagos, & Durgin, 2011; Witt, 2011b). And in an especially comprehensive replication attempt, Woods, Philbeck, and Danoff (2009) ran one replication of Proffitt et al. (2003) and three replications of Witt et al. (2004), failing to find the predicted effect in all cases. Such investigations unavoidably bear on any positive assessment of the paternalistic vision findings; wrestling over theoretical details is of little use if the findings fail to survive empirical scrutiny. However, the paternalistic vision hypothesis wears thick empirical armor and has scores of findings to its name (several of which have indeed been replicated10). It is for this reason that a comprehensive, generalizable, alternative account is needed. Fortunately, further empirical evidence points directly to such an account.

Judgment, not perception: Task demands

In perhaps the single most important finding pertaining to the dispute over paternalistic vision, Durgin et al. (2009) ran a version of the classic backpack/slant experiment (Bhalla & Proffitt, 1999), adding to the two usual conditions (backpack and no backpack) a third condition in which subjects wore a backpack accompanied by a deceptive “cover story” about the backpack’s purpose. (The backpack allegedly contained electromyographic equipment to monitor ankle-flexion signals, and even included a whirring fan for effect.) Tellingly, merely providing this plausible alternative explanation for the backpack’s presence eliminated the effect of wearing a backpack on slant estimation. Subjects wearing unexplained backpacks indeed gave greater slant estimates than did those without backpacks, but subjects who wore a backpack accompanied by the deceptive cover story gave estimates indistinguishable from those of unencumbered subjects. The researchers concluded that subjects with unexplained backpacks sought—and found—a connection between backpacks and perceived slant (nearly all subjects said so themselves in debriefing) and then complied with the demand to inflate their slant estimates. Subjects in the cover-story condition, however, were satisfied with the reason offered for the backpack’s presence and so pursued no such link. This suggests that backpack effects and related findings could be products of demand characteristics—the implicit cueing of experimental predictions to subjects, by experimenters or by the task itself—rather than effects of effort or ability on spatial perception.

It has been protested (Proffitt, 2009; Witt, 2011a; also Goldman, 2012) that Durgin et al.’s (2009) use of a 2-m wooden ramp rather than an expansive hill invalidates any general conclusions inferable from the study, because “the relative difference in the amount of energy required to walk 1 m [i.e., halfway] up a ramp with and without the backpack is probably not enough to produce a reliable change in perception” (Witt, 2011a, p. 203). However, this line of criticism is misplaced. Durgin et al. were not attempting to replicate the original backpack study; they were simply trying to show that offering subjects unexplained backpacks and asking for slant estimates bears substantial experimental demand that can bias those estimates and is therefore a burden-shifting confound that must be controlled for (see also Russell & Durgin, 2008; at any rate, subjects in real-hill experiments also say they believe the backpack is supposed to inflate slant estimates; Durgin, Klein, Spiegel, Strawser, & Williams, 2012). And at this they surely succeeded, first by successfully finding a backpack effect on slant judgments—with a measly ramp, no less!—and then eliminating that effect using their clever demand-reduction manipulation. Whether climbing the ramp would have been taxing enough to elicit a paternalistic perceptual effect is beside the point, which is that unexplained backpacks bias slant estimates.11

Demand has since been shown to make the difference in several additional cases. For example, explicitly informing backpack-wearing subjects about compliance effects eliminates the backpack’s influence on slant estimates, even for real-world hills (Durgin et al., 2012). And when climbing effort is manipulated but demand is not—by having subjects estimate the slant of either a staircase or an escalator—no effect of required effort is found (Shaffer & Flint, 2011). Conversely, manipulating belief but not ability affects spatial judgments in just the way one would expect if demand explained the results. For example, falsely informing subjects that a recently ingested diet soda was in fact sugary decreases slant estimates (Williams, Ciborowski, & Durgin, 2012), telling subjects that a golf club once belonged to a famous golfer increases estimates of golf-hole size in a putting task (C. Lee, Linkenauger, Bakdash, Joy-Gaba, & Proffitt, 2011), and telling subjects that some darts to be thrown at a target are actually defective eliminates the correlation between throwing accuracy and size estimation (Wesp & Gasper, 2012). The demand account earns even further support from a more unlikely source. When backpack-wearing subjects were found to give shallower slant estimates with close friends nearby than when alone, the preferred interpretation was an effect of “psychosocial resources” on perceived slant (Schnall et al., 2008). Although this was already a somewhat incongruous explanation (psychosocial resources, of course, do not actually improve hill-climbing ability), Durgin et al. (2009) note that this finding may more parsimoniously favor the demand account: The social support of a friend may have simply reduced the pressure to go along with the experimental demand of wearing a backpack (see Asch, 1956).

Most paternalistic vision studies give ample reason to worry about this alternative account’s reach. Consider, for example, the investigations of athletic skill and size judgments of sporting equipment. These experiments had no manipulations to speak of—each subject performed the same task and made the same judgment. Moreover, the observed effects show what Witt (2011a) calls “functional specificity,” in that “the direction of the effect is specific to the goal of the task” (p. 204). For example, softballs look bigger to hot-hitting batters, but tennis nets look smaller to successful tennis players (although see Cañal-Bruland & van der Kamp, 2009). Could even these findings be explained by demand and response bias? As noted in these articles’ introductions, these experiments—and, crucially, their hypotheses—were inspired by the relevant sport’s respective folklore. For example, Witt and Proffitt (2005) quote a hall-of-fame baseball player who remarked that a cold streak at the plate feels like “swinging at aspirins.” But such quotes (although not unambiguously about spatial perception in the first place) actually favor the demand account: If a piece of sport legend is popular enough to motivate experimental hypotheses, then surely the experimental subjects themselves (who actually play the sport) can generate such hypotheses, too. There is every reason to think, then, that demand should be equally “functionally specific” in these studies and could bias responses accordingly.

Indeed, it is difficult to find a paternalistic vision study not susceptible to this alternative account, including even those that explicitly defend against it. Consider, for example, that wielding a baton reduced distance estimates only if subjects actually used the baton to reach, which prompted the conclusion that “tool-use affects perceived distance, but only when you intend to use it” (Witt et al., 2005, p. 880). Witt (2011a) asserts that “It is difficult to account for these results with a nonperceptual explanation. For example, why would subjects have adjusted their distance judgments when holding and reaching [with] the tool but not when just holding the tool?” (p. 204). But a demand-based account of these findings could be quite straightforward. For example, confounded with subjects’ intentions to reach were the experimenter’s instructions to reach—subjects who simply held the baton and made distance estimates were never told what the baton was for. Once subjects were told to use the baton for reaching, however, the hypothesized connection between the two became clear, and the demand took effect.12

To be sure, the possibility that demand could contaminate spatial judgments has been acknowledged for some time (e.g., Proffitt et al., 2003), and several steps have since been taken to control for such factors. One promising defense against demand, as Witt (2011a) rightly suggests, is the use of “opaque manipulations” (p. 204) that do not telegraph the subject’s experimental condition or the experimenters’ hypotheses about that condition. Unfortunately, this strategy has foundered in practice. Witt cites the study of sugar consumption and slant judgment as such an opaque manipulation: Subjects drank either a sugary beverage or an artificially sweetened beverage, and there were between-group differences in slant estimates despite evidence that subjects could not identify their drink condition (Schnall et al., 2010). However, omitted from later discussions of these findings (e.g., Proffitt & Linkenauger, 2013; Witt, 2011a) is that subjects in the sugar experiments wore heavy backpacks during slant estimation. We know that this creates demand to inflate slant estimates; perhaps, then, sugar-depleted subjects were just more likely to feebly go along with such demand or at least were more likely to judge the backpack as more burdensome and so more severely inflate their estimates. Conveniently, exactly this hypothesis was recently confirmed. Although drinking a sugary beverage indeed lowers backpack-wearers’ slant estimates, instructing subjects to ignore the backpack eliminates the effect of sugar consumption on slant judgments (Durgin et al., 2012)—just as predicted by an alternative account appealing to compliance with backpack-induced demand. Even when steps were taken to control for demand and response bias, they crept in and undermined what might otherwise have been compelling findings (see also Ontiveros et al., 2011, and Witt, 2011b, on indirect measures).