More about Names Measuring Heterogeneity Gini-Simpson, or Blau - PowerPoint PPT Presentation

More about Names

Measuring Heterogeneity Gini-Simpson, or Blau Index R is “richness” or the number of types, e.g. total R ∑ number of names p 2 1 − λ = 1 − i p is the relative proportion of i =1 each type, e.g. the number of children with a specific name / total number of children.

Measuring Heterogeneity Shannon Index R is “richness” or the number of types, e.g. total R number of names ∑ H ′ = − p i ln p i p is the relative proportion of i =1 each type, e.g. the number of children with a specific name / total number of children.

NAMES AS SIGNALS

Prénoms et mention, 2019 Bac général et technologique. Positions légèrement modifiées pour éviter la superposition. Nombre de candidats Lea 5000 Thomas Manon Camille Lucas Emma Hugo Chloe Theo Marie Antoine Maxime Mathilde Clara Alexandre 18% des 2100 Juliette Clement Paul Sarah Julie Nicolas ont obtenu la mention TB Lucie Pauline Louis Quentin Laura Ines Lisa Leo Arthur Alexis Julien Marine Juliette Tom 2000 Oceane Baptiste Valentin Pierre Louise Enzo Romain Anais Charlotte Justine Eva Nathan Adrien Mathis Clemence Benjamin Margaux Victor Jade Jeanne Florian Mathieu Emilie Jules Corentin Marion Guillaume Alice Maeva Elisa Morgane Romane Noemie Axel Simon Celia Elise Matteo Zoe 5,8% des 1100 Anthony Maxence Vincent Amelie Lola Anthony Agathe Lena Martin Amandine Carla Margot 1000 Raphael ont obtenu la mention TB Bastien Laurine Lou Melissa Solene Samuel Remi Thibault Claire Kevin Matthieu Loic Gabriel Fanny Tristan Anna Elodie Audrey Maelle Elsa Melanie Valentine Robin Jeremy Dorian Salome Ambre Yanis Axelle Alicia Flavie Eloise Laurie Damien Arnaud Antonin Julia Andrea Alexia Coline Dylan Charles Killian Aurelien Jean Nina Mael Mohamed William Emeline Clementine Estelle Matheo Coralie Lise Yann Tanguy Caroline Alizee Mateo Heloise Sacha Kenza Alexandra Clarisse Titouan Sophie Mathias Anaelle Alix Alex Adam 500 Maelys Lucile David Mehdi Etienne Ilona Laure Noe Erwan Thibaut Myriam Adele Aurelie Leonie Lilou Victoria Sara Lilian Evan Benoit Sebastien Capucine Aurore Lina Celine Francois Gregoire Cloe Florent Yasmine Cassandra Laetitia Charline Aymeric Nolwenn Gaetan Gabrielle Candice Remy Augustin Angele Constance Esteban Cecile Louna Marius Marina Rayan Rachel Alan Marc Felix Enora Ludivine Emilien Jessica Perrine Jordan Luca Ophelie Elena Helene Apolline Timothee JohannaJonathan Melina Gauthier Fabien Flora Loris Luna Gaelle 300 Leila Ludovic Fiona Matthias Oriane Josephine Mathys Victoire Yannis Noah Sofiane Malo Cedric Kylian Cassandre Elea Maud Kilian Leana Leane Amine Brice Anne Tiphaine Sabrina Eliott Diane Charlene Olivia Alban Florine Dimitri Bryan Ugo Anissa Yoann Faustine Ryan Eugenie Samy Lauriane Olivier Yohan Garance Oscar Mailys Eleonore Gabin Emile Mickael Tony Julian Luc Emmanuel Justin Ninon Lou − Anne Teo Morgan Rose Roxane Sylvain Yassine Bilal Allan Imane Amaury Joris Thibaud Assia Jean − Baptiste Eve Joseph Auriane Ethan Melvin Berenice Cyril Samantha Pablo Sofia Timothe Marianne Astrid Orlane Lila Maria Lorenzo Edouard Floriane Daniel Elias Adeline Kelly Xavier Jeremie Steven Noa Flavien 0.0% 5.0% 10.0% 15.0% 20.0% Proportion de mention « très bien » Résultats provisoires. Réalisation Baptiste Coulmont | http://coulmont.com/bac/

80% N = 30 Percent of Evaluators Who Cited “Fit” 70% as Top Evaluative Criterion N = 26 60% 50% 40% N = 16 30% 20% 10% 0% Law Firms Investment Banks Consulting Firms Interpersonal Skills Technical Skills Figure 2. Percentage of Evaluators Who Ranked Fit as Their Most Important Criteria in Job Interviews by Firm Type ( N = 120) Note : These numbers correspond to the percent of evaluators in each type of firm who—in research interviews—ranked fit as the most important criterion they use to assess applicants in job interviews. Evaluators were asked to describe the specific criteria they use to assess candidates in interviews. I then asked them to force-rank the criteria they had mentioned.

AUDIT STUDY A type of field experiment where trained auditors or designed audit documents are used to evaluate a real decision process for discrimination, by matching auditors on all relevant characteristics except the one being tested.