And here it is. 🙂
This is the first version of my paper. It has still a few to-do-notes, I hope that is no poblem.
Read the text „Fighting for breath“ in Tim Skerns „Writing Scientific English“ (p. 50f) and analyze its adherence to the aspects of good style.
The text “Fighting for breath” was written by Dr. Mark Porter and published in the BBC Radio Times in the year 1999. The author discusses the influence of air pollution on health problems.
We learned about good style with guidelines what were sometimes specific to scientific writing. While the given text seems to be a newspaper article, many of those rules apply here, too.
Still, I left out some negative criticism. For instance, I would point out the lack of citations in a scientific paper, but this does not seem appropriate in this case.
There is not much to criticize about this text but some minor flaws. For example, the title does not clearly state the topic and tries to be catchy. Furthermore, there are some parts of sentences that could be removed.
Additionally some words in the text were in italics, which was irritating, because it placed emphasis on words that didn’t need it. However, I am not certain if this use of cursive was intended by the original author or added later by Tim Skern.
The text showcases a lot of properties of good style. In my opinion the variety of sentence and paragraph length as well as of the sentence structure was appropriate. The active voice and the correct tenses were employed. Moreover, jargon was not used.
All in all, the author adheres to the aspects of good style.
Use the following words in your story:
Kittens, a half-eaten pizza, telepathy, magic, a radio call-in show, salt crackers, a sixpack of beer, existential angst
What a great party that was, yesterday. I met so many strange and interesting characters!
Man, there was that one guy, who believed in magic. He really tried to use telepathy on my kitten plush toy. He may have had a beer too much. Or ten.
Then there was this woman who works as a moderator at a late night radio call-in show. She constantly has to deal with people with existential angst, weird fetishes, paranoia or a combination of those things. It sounded pretty interesting, but I don’t envy her.
Time for a left-over breakfast. Salt crackers, a half-eaten pizza and a six-pack of beer are a good meal to start the day, right? Nah, not really, but I don’t have anything else in the house.
Regarding hypotheses and questions
What phenomena or properties are being investigated? Why are they of interest?
The paper proposes a new approach to the search for related and similar documents. This can be useful for document retrieval and recommendation.
Their approach is graph-based, which usually goes hand in hand with expensive graph-operations. The authors claim to circumvent this by applying the needed knowledge from the graph to the documents during a pre-processing step
Has the aim of the research been articulated? What are the specific hypotheses and research questions? Are these elements convincingly connected to each other?
The authors want to show three things:
Their approach provides higher correlation with human notions of document similarity than comparable measures.
This holds true for short documents with few annotations.
The calculation of document similarity is more efficient, compared to graph-traversal-based approaches.
To what extent is the work innovative? Is this reflected in the claims?
The work provides a new and better approach to the assessment of relatedness of documents.
Yes, this is reflected in the claims
What would disprove the hypothesis? Does it have any improbable consequences?
Experimental results that show lower correlation with human notions of document similarity than comparable measures for normal or short document lengths or a less efficient calculation of document similarity, compared to graph-traversal-based approaches would disprove their hypotheses.
What are the underlying assumptions? Are they sensible?
They assume, that graph-based methods are not fast enough and that their approach is better than other approaches in finding similar documents. Both assumptions are sensible
Has the work been critically questioned? Have you satisfied yourself that it is
I think so.
Regarding evidence and measurement
What forms of evidence are to be used? If it is a model or a simulation, what
demonstrates that the results have practical validity?
An experiment using the standard benchmark for multiple sentence document similarity.
How is the evidence to be measured? Are the chosen methods of measurement objective, appropriate, and reasonable?
They use the Pearson and Spearman correlation and their harmonic mean as well as a quality ranking using “Normalized Discounted Cumulative Gain”.
The authors state that those metrics are used in related work as well. I can’t say for sure, if those metrics are objective and appropriate, but they allow comparison to other work, which seems reasonable.
What are the qualitative aims, and what makes the quantitative measures you have chosen appropriate to those aims?
I can’t say if they are appropriate, because I don’t know anything about those measures.
What compromises or simplifications are inherent in your choice of measure?
Because they only want to measure how well relevant documents are discovered, the qualification evaluation is only used on the top elements their approach turns up.
Additionally, they use a benchmark, which may or may not replicate real data.
Will the outcomes be predictive?
I’m not really sure what this question aims at.
What is the argument that will link the evidence to the hypothesis?
Standard measures and standard benchmarks ensure that the results can at least partially confirm or disprove the hypotheses.
To what extent will positive results persuasively confirm the hypothesis? Will negative results disprove it?
As only a benchmark and not real data is used in the experiment, the results cannot totally prove or disprove the hypotheses. Nevertheless, the results can give an indication towards one or the other.
What are the likely weaknesses of or limitations to your approach?
The pre-processing step has to be done, which probably needs time.