Computer terms in French

For native English speakers, French is a painful languagemouse_mouse
to learn. Not quite as painful as learning German, though.

ordinateur (masculin): Un ordinateur est une machine électronique programmable de traitement automatique
des données comprenant les organes nécessaires à son fonctionnement autonome.
En France, dans les années 1950, on ne savait pas comment désigner ces nouvelles machines.
Certains les appelaient «calculateurs» ou «calculatrices». Le terme anglais de computer était très utilisé.
Le nom «ordinateur » a été proposé en 1955 par Jacques Perret, professeur à la Sorbonne.
From: Yahoo! Encyclopédie

A language instructor was explaining to her class that French nouns, unlike their English counterparts, are grammatically designated as masculine or feminine. Things like " chalk" or "pencil," she described, would have a gender association. For example: House is feminine -- "la" maison. In English, of course, words are of neutral gender. Puzzled, one student raised his hand and asked, "What gender is a computer?" The teacher wasn't certain which it was, and so divided the class into two groups and asked them to decide if a computer should be masculine or feminine. One group was comprised of the women in the class, and the other of men. Both groups were asked to give four reasons for their recommendation.

The men decided that computers should definitely be referred to in the feminine gender (la) because:

  • No one but their creator understands their internal logic.
  • The native language they use to communicate with other computers is incomprehensible to everyone else.
  • Even the smallest mistakes are stored in long-term memory for later retrieval.
  • As soon as you make a commitment to one, you find yourself spending half your paycheck on accessories for it.

The group of women, however, concluded that computers should be referred to in the masculine (le) gender because:

  • In order to get their attention, you have to turn them on.
  • They have a lot of data but are still clueless.
  • They are supposed to help you solve your problems, but half the time they ARE the problem.
  • As soon as you commit to one, you realize that, if you had waited a little longer, you could have had a better model