过去的偏见和生物学进步的神话。

IF 1.3 4区 生物学 Q3 BIOLOGY
Theory in Biosciences Pub Date : 2023-11-01 Epub Date: 2023-09-23 DOI:10.1007/s12064-023-00403-2
Jani Raerinne
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引用次数: 0

摘要

生物学家中流行两种观点。第一个观点与生物学的偏见有关,尤其是生物学家过去过分强调竞争的重要性。第二个想法是关于纠正偏见的进展,即生物学的偏见性质随着时间的推移而减少。为了验证这些想法,从生物学期刊上发表的文章中收集了关于相互作用主题(如竞争、捕食和互惠互利)流行程度的数据。在出版物数据中,研究偏见应该是系统性的过度和不充分强调替代的、可行的研究主题的受欢迎程度。如果这两种观点是正确的,数据应该表明,历史上占主导地位的主题的受欢迎程度随着时间的推移而降低,而历史上边缘的替代主题的受受欢迎程度则随着时间的流逝而增加。数据表明这两种观点是错误的。根据发表的数据,生物学的偏见性质随着时间的推移而增加,这是生物学倒退而非进步的标志。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Myths of past biases and progress in biology.

Myths of past biases and progress in biology.

Myths of past biases and progress in biology.

Myths of past biases and progress in biology.

Two ideas are popular among biologists. The first idea is concerned with the biased nature of biology, especially the idea that biologists have overemphasized the importance of competition in the past. The second idea is concerned with progress in correcting for biases, namely, that the biased nature of biology decreases with time. To test these ideas, data on the popularity of interaction topics, such as competition, predation, and mutualism, was collected from articles published in biology journals. Research biases should be visible in publication data as systematic over- and underemphases regarding the popularity of alternative, viable research topics. Were the two ideas correct, data should show that the popularity of a historically dominant topic(s) diminishes with time, whereas the popularity of historically marginal, alternative topics increases with time. The data show that the two ideas are false. According to publication data, the biased nature of biology increases with time, which is a sign of regress rather than progress in biology.

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来源期刊
Theory in Biosciences
Theory in Biosciences 生物-生物学
CiteScore
2.70
自引率
9.10%
发文量
21
审稿时长
3 months
期刊介绍: Theory in Biosciences focuses on new concepts in theoretical biology. It also includes analytical and modelling approaches as well as philosophical and historical issues. Central topics are: Artificial Life; Bioinformatics with a focus on novel methods, phenomena, and interpretations; Bioinspired Modeling; Complexity, Robustness, and Resilience; Embodied Cognition; Evolutionary Biology; Evo-Devo; Game Theoretic Modeling; Genetics; History of Biology; Language Evolution; Mathematical Biology; Origin of Life; Philosophy of Biology; Population Biology; Systems Biology; Theoretical Ecology; Theoretical Molecular Biology; Theoretical Neuroscience & Cognition.
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