Gendered Nouns – Intro/Update #1

My work on this project (abstract) can be roughly divided into three categories: planning and creating the survey, running the study, and analyzing/interpreting the results. As I am close to completing the first category, it seemed like a good time for an introduction/update.


The first steps in planning the survey were selecting the nouns and creating a noun-gender database for all the languages I anticipate my respondents being familiar with. I completed these two steps largely in parallel, since one of my main goals was to find nouns that have the same grammatical gender in French, Spanish, and German. These are the languages I expect to see most often, and with the most overlap, so, if there is an influence from gendered-noun languages, it will make analysis more effective if all the influences are working in the same direction. In addition, the nouns I selected have a 50/50 masculine/feminine split, which will hopefully avoid the possibility of giving participants that unpleasant “why is every answer on this test C” feeling.

My original plan was to find 30 nouns that had the same gender in French and Spanish. This seemed like a reasonable goal, since they come from the same language family, but it took longer than I expected (sun, moon, table, and chair are just a few examples of common nouns that I could not use). To further complicate the process, I decided to try to add German into this “prioritized” subgroup. Surprisingly, I was able to accomplish this, though not without including a few more obscure nouns. (My current list of nouns can be found below.)


There were a few important considerations that I discussed with Professor Lunden in terms of designing the survey. At first, when we were assuming that I would not be able to find 30 same-gender nouns in Spanish, French, and German, I would have had to include a neuter option to account for those who would be potentially influenced by knowledge of German (or other languages with neuter nouns). Therefore, I would have had to strongly encourage people in the instructions to not just always pick neuter. Since all of my nouns are currently only either masculine or feminine in my included languages, this is no longer as much of a concern. However, I will still include similar encouragement in an attempt to make sure respondents will try to answer every question.

In addition, we decided it was important that respondents be able to easily return to previous questions and change their answers, since, for example, seeing a dog might make them decide that a cat was less masculine than they had originally thought. This was one of the primary reasons we chose SurveyMonkey over other possibilities – it was the only service that clearly stated it had this capability.

Currently, the instructions read: “On the following page, you will see a series of images of nouns. Please do your best to identify each of these nouns as either masculine or feminine. An answer may not immediately come to mind, but try to imagine which gender you most strongly associate with each noun. You may scroll back to an image to change your answer at any time. On the final page, please answer the demographic questions to the best of your ability.”


Finally, I have several post-study questions designed to collect the necessary demographic data for my analysis. First, every respondent will fill in their native language(s), defined linguistically as the language(s) they learned and used regularly before age 6. Then participants will be asked whether they speak or have ever studied any other languages. Those who answer no will be done with the survey, and their responses will automatically be counted as those of monolingual English speakers. Those who answer yes will be directed to give more information – which other language(s) they have spoken/studied, for how long, and how recently. I am also considering asking participants to self-evaluate their familiarity with this language(s), or I may stick with an evaluation based on the length and recency of their study. Based on this information, I will be able to create the necessary analytical subgroups of languages and familiarity-levels.


Going forward, my next step is to finalize the survey. I have done as much work as I can using the free version of SurveyMonkey, but I will need to add the last few questions and some of the logic elements once I get home from my study-abroad program and buy a month of the full version. Then, most of my time will be devoted to running the study through sharing the link everywhere I can and contacting people personally to ask them to participate. I am planning to report back at the end of this stage, before I begin my analysis.


  • ball
  • hand
  • umbrella
  • sky
  • dog
  • cat
  • lamp
  • coin
  • lipstick
  • balloon
  • church
  • plant
  • coffee
  • gas station
  • factory
  • bus
  • library
  • foot
  • street
  • tree
  • pullover
  • fish
  • island
  • crosswalk
  • strawberry
  • flower
  • loom
  • card (greeting)
  • mortar (and pestle)
  • pill

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