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genderBR 1.3.0

This is a new version of the genderBR package that includes a new function: get_gender_nn(), which uses a character-level neural network to predict gender from Brazilian first names. This model can generalise to names not present in the IBGE census dataset, so it can be used as a complement to the existing functionality in the package. The release also includes some improvements, tests, and documentation updates.

  • get_gender_nn() is a new exported function that uses a character-level neural network to predict gender from Brazilian first names. Unlike get_gender(), this function can generalise to names not present in the IBGE census dataset.
  • Added clear_nn_cache() to manage the in-memory model cache.
  • Added download_gender_model(), an internal function that handles downloading and caching the neural network model weights and vocabulary from Hugging Face.
  • Replaced iconv() with chartr() for stripping accents in name cleaning. The previous approach relied on iconv(name, to = "ASCII//TRANSLIT"), which is platform-dependent and returns NA on macOS for accented names (e.g., "joão"). The encoding argument in get_gender, get_gender_nn, and map_gender is now deprecated and will be removed in a future version.
  • Improved test coverage for the new function and edge cases.
  • Added torch to Imports; luz and httr2 to Suggests.

genderBR 1.2.0

  • Added support for IBGE's 2022 census data API, updating the default year to 2022 in get_gender.
  • Internal dataset nomes now includes probabilities for 2010 and 2022 (prob_fem10, prob_fem22) and is used when internal = TRUE. This data covers 141,742 unique Brazilian first names.
  • Replaced all uses of %>% with the base |> operator, thus removing the magrittr dependency (requires R 4.1.0 or higher).
  • Switched data manipulation backend to data.table for faster joins and removed dplyr/tibble dependencies.
  • Updated tests to cover new features and changes.
  • Added a section on ethical considerations in the README.

genderBR 1.1.1

In this version, a few improvements and bug fixed were introduced. Most important, connection errors now return informative messages to users.

  • map_gender and get_gender now return informative error messages when reach timeout
  • get_gender function better handles non-ASCII characters
  • Documentation expanded to notify users that IBGE's API does not work with UTF-8 special characters
  • Magritte's pipe exported

genderBR 1.1.0

In this minor release, the genderBR package was improved in two ways. First, bugs and some minor issues were fixed, making the package's functions more stable. Second, the package now contains an internal dataset with all the names reported by the IBGE's Census that is used by the get_gender function to predict gender from Brazilian first names. Therefore, classifying a vector with more than 1,000 names takes no more than a few seconds now. Overall, these are the improvements:

  • Added a NEWS.md file to track changes to the package.
  • Added input checks to the get_gender function.
  • Reduce the time between requests to the IBGE's Census API.
  • Fixed a problem on vectorization in the internal round_guess funcion.
  • Included an internal dataset with all Brazilian first names and their predicted gender extracted from the IBGE.
  • Update the get_gender function to work with internal data.