Perfect.
 
Beth Cherry
___________
Sr. Creative Consultant
EnFORM Technology
713.350.1860
 
-----Original Message-----
From: Robinson, Misty 
Sent: Monday, October 22, 2001 8:59 AM
To: ANGELO DAVIS (E-mail); Betty Godfrey (E-mail); Augusta Burney (E-mail) (E-mail); Brentley S. Felton (E-mail); Devon Anderson (E-mail); Rae Rae (E-mail); Sevena (E-mail); Landry, Ashley; Cherry, Beth; Lindner, Fred
Subject: FW: Computer in French
 
 
-----Original Message-----
From: Bernal, Claudia 
Sent: Monday, October 22, 2001 8:45 AM
To: EnFORM - Admin Assistants; EnFORM - HelpDesk; Nguyen, Viet
Subject: FW: Computer in French
 
----- Original Message -----
       A language instructor was explaining to her class that French nouns,
       unlike their English counterparts, are grammatically
       designated as masculine or feminine.
       "House," in French, is feminine - "la maison."
       "Pencil," in French, is masculine - "le crayon."
       One puzzled student asked, "What gender is computer?"
       The teacher did not know, and the word wasn't in her French
       dictionary. So for fun she split the class into two groups appropriately
      enough, by gender, and asked them to decide whether "computer" should be a
      masculine or feminine noun. Both groups were required to give four
      reasons for their recommendation.
        The men's group decided that computers should
        definitely be of the feminine gender ("la computer"), because:
         1. No one but their creator understands their
            internal logic;
         2. The native language they use to communicate with
            other computers is incomprehensible to everyone else
         3. Even the smallest mistakes are stored in long-term
            memory for possible later retrieve; and
         4. As soon as you make a commitment to one, you find
            yourself  spending half your pay check on accessories for it.
       The women's group, however, concluded that computers
       should be masculine ("le computer"), because:
        1. In order to do anything with them, you have to
           turn them on
        2. They have a lot of data but still can't think for themselves
        3. They are supposed to help you solve problems, but
           half the time they are the problem; and
        4. As soon as you commit to one, you realize that if
           you'd waited a little longer, you could have gotten a better model.
         



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