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.

Let me give you an example: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequence model. Large-Scale Chinese Short Text Summarization Dataset (LCSTS) is constructed by BIBREF1 . The dataset consists of more than 2.4 million text-summary pairs in total, constructed from a famous Chinese social media microblogging service Weibo.
Question: Are results reported only for English data?
The answer to this example can be: No
Here is why: Based on the context, the dataset is constructed from a famous Chinese social media microblogging service Weibo.

OK. solve this:
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?
Answer:
only 1 in 9 qualitative papers in Human-Computer Interaction reported inter-rater reliability metrics low-effort responses from crowdworkers