In a scenario characterized by unpredictable developments, such as the recent COVID-19 pandemic, epidemiological models have played a leading part, having been especially widely deployed for forecasting purposes. In this paper, two real-world examples of modeling are examined in support of the proposition that science can convey inconsistent as well as genuinely perspectival representations of the world. Reciprocally inconsistent outcomes are grounded on incompatible assumptions, whereas perspectival outcomes are grounded on compatible assumptions and illuminate different aspects of the same object of interest. In both cases, models should be viewed as expressions of specific assumptions and unconstrained choices on the part of those designing them. The coexistence of a variety of models reflects a primary feature of science, namely its pluralism. It is herein proposed that recent over-exposure to science’s inner workings and disputes such as those pertaining to models, may have led the public to perceive pluralism as a flaw—or more specifically, as disunity or fragmentation, which in turn may have been interpreted as a sign of unreliability. In conclusion, given the inescapability of pluralism, suggestions are offered as to how to counteract distorted perceptions of science, and thereby enhance scientific literacy.

在事态发展不可预测的情况下，例如最近的 COVID-19 大流行，流行病学模型发挥了主导作用，特别广泛用于预测目的。在本文中，研究了两个现实世界的建模示例，以支持科学可以传达对世界的不一致且真实的透视表征这一命题。相互不一致的结果基于不相容的假设，而透视结果基于相容的假设并阐明同一感兴趣对象的不同方面。在这两种情况下，模型都应被视为特定假设的表达和设计者的不受约束的选择。多种模型的共存反映了科学的一个主要特征，即科学的多元化。本文提出，最近对科学内部运作和争议（例如与模型有关的争议）的过度曝光可能导致公众将多元主义视为一种缺陷，或者更具体地说，视为不统一或分裂，这反过来可能被解释为作为不可靠的标志。总之，鉴于多元化的不可避免性，提出了如何抵消扭曲的科学观念，从而提高科学素养的建议。