In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

Which events authors choose to include in their history, which they leave out, and the way the events chosen relate to the march are crucial factors in conveying bias. 
 Question: What factors contribute to interpretive biases according to this research?
Which events authors choose to include in their history, which they leave out, and the way the events chosen relate to the march

A meta-research study found only 1 in 9 qualitative papers in Human-Computer Interaction reported inter-rater reliability metrics BIBREF31. Another related area are meta-research and methods papers focused on identifying or preventing low-effort responses from crowdworkers — sometimes called “spam” or “random” responses, or alternatively ”fraudsters” or ”cheaters.” Rates of “self-agreement” are often used, determining if the same person labels the same item differently at a later stage. 
 Question: What are the key issues around whether the gold standard data produced in such an annotation is reliable? 
 only 1 in 9 qualitative papers in Human-Computer Interaction reported inter-rater reliability metrics low-effort responses from crowdworkers

In this paper, I introduce an interpretable word embedding model, and an associated topic model, which are designed to work well when trained on a small to medium-sized corpus of interest. I tested the performance of the representations as features for document categorization and regression tasks. The results are given in Table TABREF26 . For document categorization, I used three standard benchmark datasets: 20 Newsgroups (19,997 newsgroup posts), Reuters-150 newswire articles (15,500 articles and 150 classes), and Ohsumed medical abstracts on 23 cardiovascular diseases (20,000 articles). I I also analyzed the regression task of predicting the year of a state of the Union address based on its text information.  
 Question: What supervised learning tasks are attempted with these representations?

document categorization regression tasks