The Technique of Clear Writing.

By R. Gunning. 1968

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Citations in the corpus

Explainable Recommendation: A Survey and New Perspectives (2018, background): “The explanation quality can also be evaluated in terms of readability measures, such as Gunning Fog Index (Gunning, 1952), Flesch Reading Ease (Flesch, 1948), Flesch Kincaid Grade Level (Kincaid et al.”
Human-Explainable Features for Job Candidate Screening Prediction (2017, methodology): “More specifically, we used 8 measures as features for the Readability representation: ARI [22], Flesch Reading Ease [12], FleschKincaid Grade Level [15], Gunning Fog Index [13], SMOG Index [16], Coleman Liau Index [8], LIX, and RIX [2].”
Goal Ambiguity in U.S. Federal Agencies (2005, background): “The higher the GFI, the harder the written passage is to comprehend (Gunning 1968).”
Reading Level Assessment Using Support Vector Machines and Statistical Language Models (2005, methodology): “Similarly, the Gunning Fog index is based on the average number of words per sentence and the percentage of words with three or more syllables (Gunning, 1952).”
How Readability Shapes Social Media Engagement (2018, background): “Word complexity is often proxied as word length or number of syllables (e.g., Flesch, 1948; Gunning, 1952; McLaughlin, 1969).”
Finding high-quality content in social media (2008, methodology): “Several measures of text readability have been proposed, including the Gunning-Fog Index [15], the Flesch-Kincaid Formula [21], and SMOG Grading [23].”
Self-Induced Curriculum Learning in Self-Supervised Neural Machine Translation (2020, methodology): “For this, we apply a modified version of the Gunning Fog Index (GF) (Gunning, 1952), which is a”
Association of health literacy with diabetes outcomes. (2002, unknown): “004 Medicaid 93 (23) 33 (21) 12 (22) 48 (24)”
The Child–Adolescent Perfectionism Scale (2016, methodology): “Standard formulae (e.g., Flesch, 1979; Gunning, 1952) for reading-level analyses of the items and instructions established that a Grade 3 reading level is required.”
The Evolution of 10-K Textual Disclosure: Evidence from Latent Dirichlet Allocation (2017, background): “Fog The Gunning (1952) Fog index, where Fog = 0.4 ∗(average number of words per sentence + percent of complex words), where complex words are the words in excess of two syllables.”
Accuracy of Readability Estimates' Predictions of CBM Performance. (2005, unknown): “In a review of the R-CBM literature, the authors examined 34 articles and found that 21 of the 34 articles had used either the Spache (eight articles, 1953), Fog (one article, Gunning, 1968), Fry (nine articles, 1968), Dale-Chall (three articles, 1948), Flesch-Kinkaid (one article, Flesch, 1948), or”
The impact of narrative disclosure readability on bond ratings and the cost of debt (2017, unknown): “However, given that numerous accounting studies have employed the Gunning (1952) Fog Index (Li 2008; Biddle et al. 2009; Miller 2010; Lehavy et al. 2011; Lawrence, 2013) and that Loughran and McDonald (2014a) suggest the use of 10-”
Phonological similarity effects in simple and complex span tasks (2011, methodology): “(Gunning, 1952), and SMOG (McLaughlin, 1969) indices.”