Q5 English Language Paper 1

[Gene Cryder]

Somemonths back I got into a situation where a paper with information that I considered important to prove a point was in a language I cannot understand. Since it was important but not crucial, I ended up not using the paper. Except for its abstract, which was in English, the entire paper was in this other language. It had graphs and images that I could understand without knowing the language.

But say that in a future situation I find a crucial paper in a language I don't understand: if I use Google Translate, using the paper in a situation that does not require specific information but only it's general gist, would citing it be ethically acceptable?

I think the fact that the paper is in a language you don't understand is somewhat of a red herring. Sure, it will affect the specific steps you'd take to try to understand the paper, but the ethics of "to cite, or not to cite" it is no different from a paper you don't understand written in a language you speak. You're generally supposed to provide a good-faith overview of the literature, with citations as appropriate. The fact that one paper is significantly harder to understand doesn't really change that.

My view is that it behooves you to, as far as possible*, and regardless of language, at least understand at a high level what the full papers you cite contain, and the parts of papers you use on a detailed level. Google Translate will be good enough in some cases, but for other cases it's better used as a starting point. If you find yourself doubting the machine translation it's certainly best to use it as a starting point. You might want to try to clarify uncertain points with the authors, ask a colleague (who might speak the language) for help, get a professional translation of parts of the paper, or use a secondary citation.

You cite earlier works either because you directly built on them, or to provide the background against which you are working, and to position your new contribution in the larger context of existing research.

Reiterating the main points (as I see it) of the other answers: if it's relevant, cite it... both to show your own awareness, and to acknowledge prior art, whether or not it exactly impinged on your own work.

That is, whether or not an individual can fully vet a piece of work, through difficulty with the ambient language or whatever, acknowledgement of its existence is very important, I think. Citing things is different from endorsement, and is different from a claim that one has fully checked all details, or even read the whole thing through. Just be clear, in the citation, what use you made of it, or did not.

As an example to perhaps not cite: if you happened to read arguably crack-pot documents on arXiv (for math, for example) purporting (implausibly) to do amazing things in your specialty, I think you can justify not citing... if the author has insufficient credibility, and no one else with any credibility has vouched for it. But, yes, what the heck is "credibility"? :)

I would lean to including it. Of course you need to be careful about relying on something you can't completely read but this applies to everything (even just hard math). But I would lean to more cites than less since it helps future researchers.

If you just need a datapoint (say transition temperature of a well known and noncontroversial substance), I think just taking the datapoint is fine without translation. Depending on how much more you need, you can try struggling through it with partial info, ask someone to look at it, use Google Translate, etc. If it is crucial, just pay for a translation and charge to your grant (this is not that hard, have done it).

If "to cite" is interpreted as "to include, in the 'works cited' or 'references' section of your academic work, a academic-publication-style-conformant bibliographic reference to a piece of scholarly work", it does not seem to be a good idea to include papers which you think you have understood by just reading its abstracts, its figures and tables (very likely that their titles are not in your language either) and machine-translated contents. You include a paper in your "works cited" section because you have carefully studied it, reflected upon it, analysed it against the theories and conclusions you've already known, or even carried out verification work, after which finding that the paper is of significant importance to your own study, positively or negatively. In this way you are weaving connections between past and present so that followers will see how the discipline has developed.

You do not include citations to show that you have consulted a lot of sources, or to let others know that you think this one is really important--important is a personal feeling unless quantified by, say, h-index; whether a paper is important or not is the reader's business, not yours. If a lot of authors do include this piece of literature in their works then that literature would naturally be important empirically.

That said, nothing stops you from including the article under concern in your own thesis: an academic-publication-style-conformant footnote or endnote would do well. Some professors even require their students to have both a "Works Cited" part and a "Works Consulted" part in their disseration (e.g. mine), and at least for humanities fields I have seen really serious scholars doing the same in their monograph. Also remember that the reference can be annotated as well.

in a future situation I find a crucial paper in a language I don't understand: if I use Google Translate, using the paper in a situation that does not require specific information but only it's general gist

I don't see the underlying logical connection: if a paper is really crucial to you, your study must have partially relied upon it, how then is it possible that you would be citing it only for general, non-specific purposes? Additionally, suppose that other readers knowing the same languages as you have consulted your paper and also found the paper under concern worth reading, how then will you know that they are just reading it for general gist?

This section includes recent GCSE English Language past papers (9-1) (8700) from AQA. You can download each of the AQA GCSE English Language past papers and marking schemes by clicking the links below.

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AI language models are a key component of natural language processing (NLP), a field of artificial intelligence (AI) focused on enabling computers to understand and generate human language. Language models and other NLP approaches involve developing algorithms and models that can process, analyse and generate natural language text or speech trained on vast amounts of data using techniques ranging from rule-based approaches to statistical models and deep learning. The application of language models is diverse and includes text completion, language translation, chatbots, virtual assistants and speech recognition. This report offers an overview of the AI language model and NLP landscape with current and emerging policy responses from around the world. It explores the basic building blocks of language models from a technical perspective using the OECD Framework for the Classification of AI Systems. The report also presents policy considerations through the lens of the OECD AI Principles.

English Language Learners (ELLs), a diverse group making up nearly 5 million of the K-12 student population in the US, face the layered challenge of acquiring a new language while learning core academic subjects.

Meeting their academic needs is one of the biggest challenges facing US educators this year, as disproportionalities in pandemic-induced learning losses are exacerbating existing achievement gaps between ELLs and non-ELLs.

With students being able to receive live help in their preferred language across core subjects, Paper serves as a comfortable, safe, and secure learning environment that helps students feel more confident in their school work.

Bunch, G., Kibler, A., & Pimentel, S. (2012). Realizing opportunities for ELLs in the Common Core English Language Arts and disciplinary literacy standards. In Proceedings of the Understanding Language conference.

van Lier, L., & Walqui, A. (2012). Language and the common core state standards. Commissioned Papers on Language and Literacy Issues in the Common Core State Standards and Next Generation Science Standards, 94, 44.

Bailey, A. L., & Wolf, M. K. (2012). The challenge of assessing language proficiency aligned to the Common Core State Standards and some possible solutions. In Understanding Language Conference, Stanford University, Stanford, CA.

Brisk, M. E., & Proctor, C. P. (2012). Challenges and supports for English language learners in bilingual programs. Commissioned Papers on Language and Literacy Issues in the Common Core State Standards and Next Generation Science Standards, 94, 115.

Abedi, J., & Linquanti, R. (2012, January). Issues and opportunities in improving the quality of large scale assessment systems for ELLs. In Paper presented the Understanding Language conference, Palo Alto, CA.

Lucas, R., & Willinsky, J. (2012). Online Community for Teachers of English Language Learners. Commissioned Papers on Language and Literacy Issues in the Common Core State Standards and Next Generation Science Standards, 94, 128.

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