address1

The data were collected by the TEPP team (FR CNRS 2042) between December 2008
and January 2009. A candidate is defined by the variables ("gender","origin",
"mediaexp"). The variable "reput" creates a sample separation.
<ul>
<li>offer: add number.</li>
<li>date: date of the application.</li>
<li>sentorder: order in which the application was sent.</li>
<li>callback: TRUE if there was a non negative callback.</li>
<li>fname: first name (forename).</li>
<li>lname: last name (family name, surname).</li>
<li>origin: all the candidates are French, the origin is suggested by the
name, F = France, M = Morocco.</li>
<li>gender: Woman or Man.</li>
<li>city: candidate location.</li>
<li>reput: reputation of the city, P = privileged, U = Unprivileged.</li>
<li>mediaexp: strong negative mediatic exposure, Yes or No.</li>
</ul>

datasets

In discrimination experiments candidates are sent on the same test (e.g. job, house rental) and one examines whether they receive the same outcome. The number of non negative answers are first examined in details looking for outcome differences. Then various answering rates and their exacts confidence intervals are computed. Last, exact and asymptotic discrimination tests are performed. Graphical methods are also available.

Emmanuel Duguet

callback

Computes Statistics from Discrimination Experimental Data

David Gray

Loïc du Parquet

Yannick L'Horty

Rémi Le Gall

Noam Léandri

Pascale Petit

Florent Sari

address1 function

A data frame with 3684 rows and 11 variables

Format

Origin/Gender discrimination and strongly negative mediatic exposure
(information technologist) — address1

Origin/Gender discrimination and strongly negative mediatic exposure
(information technologist)

address1: Origin/Gender discrimination and strongly negative mediatic exposure (information technologist)

Description

Usage

Arguments

Format

References