We assess the communications of 37 airlines on their own websites regarding voluntary carbon offsets (VCO) to determine the extent to which they are either trustworthy or misleading. We propose an innovative coding framework that captures the trustworthy or misleading attributes of the messages as they are applied to: i) the type of claim (product, process, fact or image), and ii) the nature of the claim (fibbing, hidden trade-off, no proof, vagueness, irrelevance, lesser of two evils or worshiping false labels). We deploy a quantitative, multi-method approach that combines content analysis and discrete choice modelling, and we corroborate the taxonomy developed with lexical analysis. We identify the various factors that affect the pattern of 56% of claims being trustworthy and 44% being misleading. We demonstrate how a combined study of the trustworthy or misleading characteristics of communications provides more learning opportunities than studying either individually.

我们评估了 37 家航空公司在其网站上就自愿碳抵消 (VCO) 进行的沟通，以确定它们的可信度或误导性。我们提出了一种创新的编码框架，可以捕获消息的可信或误导性属性，因为它们应用于：i) 声明的类型（产品、过程、事实或图像），以及 ii) 声明的性质（谎言、隐藏权衡，没有证据，含糊不清，无关紧要，两害相权取其轻或崇拜虚假标签）。我们部署了一种定量的、多方法的方法，结合了内容分析和离散选择建模，我们证实了用词法分析开发的分类法。我们确定了影响 56% 的声明值得信赖和 44% 具有误导性的模式的各种因素。