diff --git a/comparing_the_written_language_of_scientific_and_non_scientific_sources.md b/comparing_the_written_language_of_scientific_and_non_scientific_sources.md
index 5b83d598abf7a58a468a8f0d0076380b6083b2be..6bfec750c335bdad8803cac874098d691cba369b 100644
--- a/comparing_the_written_language_of_scientific_and_non_scientific_sources.md
+++ b/comparing_the_written_language_of_scientific_and_non_scientific_sources.md
@@ -2,7 +2,7 @@
 
 ### [Journal of Open Source Software](https://joss.readthedocs.io/en/latest/submitting.html)
 
-# Comparing the Written Language of Scientific and Non-scientific Sources
+# Comparing the Readability of Scientific and Non-scientific Sources
 
 ## Authors
 Russell Jarvis, Patrick McGurrin
@@ -12,45 +12,43 @@ To ensure writing is accessible to a general population, writers must consider t
 
 In the age of growing science communication, this tendency for scientists to use more complex language can carry over when writing in more mainstream media, such as blogs and social media. This can make public-facing material difficult to comprehend, undermining efforts to communicate scientific topics to the general public.
 
-To address this, we created a tool to analyze complexity of a given scientist’s work relative to other writing sources. The tool first quantifies existing text repositories of defined complexity, which are then used as a reference to contextualize the readability of the user-selected written work. 
+To address this, we created a tool to analyze complexity of a given scientist’s work relative to other writing sources. The tool first quantifies existing text repositories with varying complexity, and subsequently uses this output as a reference to contextualize the readability of user-selected written work. 
 
-We believe this tool uses a data-driven approach to provide insightful, statistical insights to the user about their writing. We hope it will help scientists interested in science communication to make their published work more accessible to a broad audience, and with hope lead to an improved global communication and understanding of complex topics.
+While other readability tools currently exist to report the complexity of a single document, this took uses a more data-driven approach to provide authors with insights into the readability of their published work with regard to other text repositories. This enables them to monitor the complexity of their writing with regard to other available text types, and with hope will lead to the creation of more accessible online material.
 
 ## Methods
-We built a web-scraping and written text analysis infrastructure by extending many existing Free and Open Source (FOS) tools, including Google Scrape, Beautiful Soup, and Selenium.
+We built a web-scraping and text analysis infrastructure by extending many existing Free and Open Source (FOS) tools, including Google Scrape, Beautiful Soup, and Selenium.
 
-### Text Metrics to Assess Language Complexity
-1.  Text-stat - measures text reading level (complexity)
-2.  The Natural Language Processing Tool Kit (NLTK) - measures text subjectivity and sentiment
-3.  Search Engine Factors - records page rank
-4.  LZW (de-)compression-ratio - measures information entropy
-5.  Cluster centers - measures clustering of data when organized using complexity, sentiment, word length and compression  ratios
+### Text Metrics to Assess Readability
+| Text Metric |   Description of Measurement |
+|----------|----------|
+| Text-stat                                        | text reading level (complexity) |
+| The Natural Language Processing Tool Kit (NLTK)  | text subjectivity and sentiment |
+| Search Engine Factors      | page rank  |
+| LZW (de-)compression-ratio | information entropy of text |
+| Cluster centers            | clustering of text when organized using complexity, sentiment, word length and compression  ratios   |
 
 These metrics are combined to formulate a single readability score for each scraped item. 
 
 ### Reference Texts used for Analysis
 We include a number of available reference texts with varying complexity. 
 
-1. Upgoer5 - a library using only the 10,000 most commonly occurring English words[3].
-2. Wikipedia - a free, popular, crowdsourced encyclopedia that is generated from self-nominating volunteers.
-3. Postmodern Essay Generator (PMEG) - generates output consisting of sentences that obey the rules of written English, but without restraints on the semantic conceptual references [4].
-4. ART Corpus - a library of scientific papers published in The Royal Society of Chemistry (RSC) [5].
-
-
-| Text Source | Mean Complexity | Unique Words |
+| Text Source | Mean Complexity | Description |
 |----------|----------|:-------------:|
-| Upgoer 5                                     | 6                               | 35,103 |
-| Wikipedia                                    | 14.9                            | -  |
-| Post-Modern Essay Generator                  | 16.5                            | -  |
-| Art Corpus                                   | 18.68                           | 2,594 |
+| Upgoer 5 [3]                             | 6   | a library using only the 10,000 most commonly occurring English words |
+| Wikipedia                               | 14.9 | a free, popular, crowdsourced encyclopedia   |
+| Post-Modern Essay Generator (PMEG) [4] | 16.5 | generates output consisting of sentences that obey the rules of written English, but without restraints on the semantic conceptual references   |
+| Art Corpus [5]                       | 18.68  | a library of scientific papers published in The Royal Society of Chemistry |
 
 ### Plot Information 
-The results of this tool generate a histogram binned by readability score, which is initially populated exclusively by the ART corpus. We use the ART corpus because it is a pre-established library of scientific papers. After entering an author's name, a graph displays the mean writing complexity of this author against a distribution of content from ART corpus.
+Entering an author name into the tool generates a histogram binned by readability score, which is initially populated exclusively by the ART corpus data. We use this data because it is a pre-established library of scientific papers. The resulting graph displays the mean writing complexity of the entered author against a distribution of ART corpus content.
+
+Upgoer5, Wikipedia, and PMEG libraries are also scraped and analyzed, with their mean readability scores applied to the histogram plot to inform the user of the level of complexity of the entered author's work. 
 
-Upgoer5, Wikipedia, and PMEG libraries are also scraped and analyzed, with their mean readability scores applied to the histogram plot. 
+We also include mean readability scores from two scholarly reference papers, Science Declining Over Time [1] and Science of Writing [6], which discuss writing to a broad audience in an academic context. We use these to demonstrate the feasability of discussing complex content using more accessible language.
 
 ### Reproducibility
-A Docker file and associated container together serve as a self-documenting and extremely portable software environment clone to ensure reproducibility given the hierarchy of software dependencies.
+A Docker file and associated container together serve as a self-documenting and portable software environment clone to ensure reproducibility given the hierarchy of software dependencies.
 
 ## Results
 Data are available here: [Open Science Framework data repository](https://osf.io/dashboard).
@@ -77,14 +75,9 @@ docker run -v $HOME/data_words russelljarvis/science_accessibility_user "R Gerki
 
 
 ## Future Work
-We have created a command line interface (CLI) for using this tool. However, we aim to expand this to a web application that will be more user friendly. 
+We have created a command line interface (CLI) for using this tool. However, we aim to expand this to a web application that is more user friendly to those less familiar with coding. 
 
-Additionally, we aim to add in other text repositories well-known to the public, such as wikipedia, that have been shown to be accessible and commonly used by a general audience. In addition, we're interested in general readability of the web, and aim to add search engine queries of different and broad-ranging lists of search terms to assess readability of an eclectic range of text. These two goals would further contextualize the readability of published scientific work with regard to that engaged by the public on a more daily basis.
-
-## Conclusions
-In this document, we introduce a tool for exploring the readability of a scientist's published work with regard to other web-based repositories. While other readability tools currently exist to report the complexity of a single document, our work expands upon these tools by contextualizing the complexity of the author's work by comparing it to a variety of other text types. 
-
-We do not intend to compete with these well-established tools. In contrast, the goal is to apply a more data-driven approach to provide established academic authors with statistical insights into their body of published science work. This will allow authors to better monitor the complexity of their writing with regard to other available text types, leading to the creation of more accessible online material.
+While the readability of ART Corpus is comparable to that of other scientific journals [2], a future goal is also to incoporate a larger repository of journal articles to compute the distribution of readability. In addition, we're interested in general readability of the web, and aim to add search engine queries of different and broad-ranging lists of search terms to assess readability of an eclectic range of text. This would further contextualize the readability of published scientific work with regard to topics engaged by the public on a more daily basis.
 
 ## References
 [1] Kutner, Mark, Elizabeth Greenberg, and Justin Baer. "A First Look at the Literacy of America's Adults in the 21st Century. NCES 2006-470." _National Center for Education Statistics_(2006).
@@ -96,3 +89,5 @@ We do not intend to compete with these well-established tools. In contrast, the
 [4] Bulhak, Andrew C. "On the simulation of postmodernism and mental debility using recursive transition networks." Monash University Department of Computer Science (1996).  
 
 [5] Soldatova, Larisa, and Maria Liakata. "An ontology methodology and cisp-the proposed core information about scientific papers." JISC Project Report (2007).
+
+[6] Gopen, George D., and Judith A. Swan. "The science of scientific writing." American Scientist 78, no. 6 (1990): 550-558.