Real-world estimation: Estimation modes and seeding effects

Brown, Norman

doi:10.1016/s0079-7421(02)80011-1

Cited by 33 publications

(63 citation statements)

References 45 publications

(65 reference statements)

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“…These four observations are consistent with the influence of categorical information on location estimates (Brown, 2002;Friedman & Brown, 2000a, 2000bHuttenlocher, Hedges, & Duncan, 1991;McNamara, 1986; This research was supported by grants from the Natural Sciences and Engineering Research Council of Canada and by Grants DUE-9551939 and 9906418 from the U.S. National Science Foundation. We express our thanks to the students who participated.…”

supporting

confidence: 73%

“…Previous evidence has shown that people use an ordinal conversion strategy when asked to provide numeric estimates in knowledge domains for which the relevant facts are scarce (Brown, 2002;Brown & Siegler, 1993). For location estimates, we hypothesized that this strategy involves drawing on beliefs about the ordinal positions of the regions and their relation to global reference points to define the response range and to partition it among the regions.…”

mentioning

confidence: 99%

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Cross-cultural similarities and differences in North Americans’ geographic location judgments

Friedman

Kerkman

Brown

et al. 2005

Psychonomic Bulletin & Review

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We examined some potential causes of bias in geographic location estimates by comparing location estimates of North American cities made by Canadian, U.S., and Mexican university students. All three groups placed most Mexican cities near the equator, which implies that all three groups were influenced by shared beliefs about the locations of geographical regions relative to global reference points. However, the groups divided North America into different regions and differed in the relative accuracy of the estimates within them, which implies that there was an influence of culture-specific knowledge. The data support a category-based system of plausible reasoning, in which biases in judgments are multiply determined, and underscore the utility of the estimation paradigm as a tool in cross-cultural cognitive research.

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supporting

confidence: 73%

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confidence: 99%

Cross-cultural similarities and differences in North Americans’ geographic location judgments

Friedman

Kerkman

Brown

et al. 2005

Psychonomic Bulletin & Review

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“…This explanation of our results is related to the Bestimation modes^proposed by Brown (2002) to account for people's estimates of specific real-world quantities, such as the population of Los Angeles. One mode is numerical retrieval, in which an estimate is based on the recollection of at least one relevant numerical fact.…”

Section: Discussionsupporting

confidence: 65%

“…Within this mode, there are various processes that may occur: people may be able to directly retrieve the value of interest (3.9 million people), or retrieve a related value that must be adjusted or transformed (e.g., a few years ago the population was 3.5 million people). In the absence of such retrievable facts, Brown (2002) has suggested that people engage in an alternative mode, called ordinal conversion. This is a more complex process that involves establishing a plausible response range, then judging where the target item (e.g., the population of Los Angeles) is situated relative to other relevant items (e.g., the populations of other cities).…”

Section: Discussionmentioning

confidence: 99%

Exploring the knowledge behind predictions in everyday cognition: an iterated learning study

et al. 2015

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Making accurate predictions about events is an important but difficult task. Recent work suggests that people are adept at this task, making predictions that reflect surprisingly accurate knowledge of the distributions of real quantities. Across three experiments, we used an iterated learning procedure to explore the basis of this knowledge: to what extent is domain experience critical to accurate predictions and how accurate are people when faced with unfamiliar domains? In Experiment 1, two groups of participants, one resident in Australia, the other in China, predicted the values of quantities familiar to both (movie run-times), unfamiliar to both (the lengths of Pharaoh reigns), and familiar to one but unfamiliar to the other (cake baking durations and the lengths of Beijing bus routes). While predictions from both groups were reasonably accurate overall, predictions were inaccurate in the selectively unfamiliar domains and, surprisingly, predictions by the China-resident group were also inaccurate for a highly familiar domain: local bus route lengths. Focusing on bus routes, two follow-up experiments with Australia-resident groups clarified the knowledge and strategies that people draw upon, plus important determinants of accurate predictions. For unfamiliar domains, people appear to rely on extrapolating from (not simply directly applying) related knowledge. However, we show that people's predictions are subject to two sources of error: in the estimation of quantities in a familiar domain and extension to plausible values in an unfamiliar domain. We propose that the key to successful predictions is not simply domain experience itself, but explicit experience of relevant quantities. Keywords Everyday reasoning . Iterated learning . Bayesian inference . Cross-cultural comparisonSurvival depends upon making successful predictions about the future. This is hard enough in domains with which we are familiar but often predictions are also required in unfamiliar domains. A prosaic example is offered by the office worker who has a good understanding of how long to wait for the elevator in her building; how long should she wait in another, unfamiliar, building? If three futile minutes have already passed, should she head for the stairs? Given that these kinds of predictions are commonplace, two main questions arise: on what are the predictions based and how accurate are they? Surprisingly, there is evidence that people can make accurate predictions even in domains for which they might have limited or even no direct experience. Griffiths and Tenenbaum (2006) asked participants to estimate quantities in several different domains that varied in familiarity (though they were collectively referred to as Beveryday phenomena^), such as male life-spans, the baking time of cakes, movie grosses, and the lengths of pharaohs' reigns. Participants were asked to make a single prediction for each domain based on an observed (probe) value of that quantity. For example, they could be asked: given that a man is 39 years old,...

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“…In this approach, when people make numeric latitude estimates, we assume that they use an ordinal conversion strategy (Brown, 2002b;Brown & Siegler, 1993) to divide the numeric range of latitudes (which are given by instruction) among the continents and whatever regions they believe lie within. Further, after deciding where North America lies within the 90 o to Ϫ90 o range, participants divide that portion of the range into mutually exclusive parts associated with each of the geographical regions.…”

mentioning

confidence: 99%

The role of categories and spatial cuing in global-scale location estimates.

Friedman¹

2009

Journal of Experimental Psychology: Learning, Memory, and Cogni

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Seven independent groups estimated the location of North American cities using both spatial and numeric response modes and a variety of perceptual and memory supports. These supports included having location markers for each city color coded by nation and identified by name, giving participants the opportunity to see and update all their estimates throughout the task, and allowing them to respond directly on a map. No manipulation mitigated the influence of categories on the judgments, but some manipulations improved within-region ordinal accuracy. The data provide evidence that the city and regional levels are independent, spatial and numeric response modalities affect accuracy differently at the different levels, biases at the regional level have multiple sources, and accurate spatial cues improve estimates primarily by limiting the use of global landmarks to partition the response space. Results support J. Huttenlocher, L. V. Hedges, and S. Duncan's (1991) theory of spatial location estimates and extend it to the domain of real-world geography.

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Real-world estimation: Estimation modes and seeding effects

Cited by 33 publications

References 45 publications

Cross-cultural similarities and differences in North Americans’ geographic location judgments

Cross-cultural similarities and differences in North Americans’ geographic location judgments

Exploring the knowledge behind predictions in everyday cognition: an iterated learning study

The role of categories and spatial cuing in global-scale location estimates.

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