Data
Below I provide links to the data and replication packages for papers where I was partly or fully responsible for generating and/or analysing the data.
Status discrimination on class
The data consists of two experimental samples (n = 401 and n = 300) of "evaluators", participants whose job it was to evaluate which of two players should do better. Each evaluator did multiple evaluations. The purpose of the data was to study discrimination on class and gender as a function of information on performance.
The data, including the scripts to replicate results, is available here: https://osf.io/dexjy/
Can cognitive dissonance explain beliefs regarding meritocracy?
The data consists of an experimental sample of "Receivers" (n = 351), who received either equal or unequal offers of money from a "Proposer" and, in some treatments, had the possibility to reject the offer. The Receivers gave their opinion on whether the offer was fair and whether the Proposer had earned the money or been given it. See the working paper here for more information on the design.
The data, including the scripts to replicate results, is available here: https://osf.io/e265w/
Status beliefs negatively affect expected university attainment of lower class students
The data comes from an experimental sample of 16-year old school children who were asked to review a series of vignettes of hypothetical students and answer whether the vignette students should be expected to go to univeristy. See the publication for more information on the design.
The data, including the scripts to replicate results, is available here: https://osf.io/qbeha/
Hiring discrimination: the influence of referrer versus applicant gender on employer decisions
The data comes from an experimental sample of Performers (n = 94), Referrers (n = 592), and Selectors (n = 1502). The Performers did a maths task and a childcare knowledge task, the Referrers reviewed their performance and decided whether to refer them to the Selectors, and the Selectors reviewed the referrals and decided whether to hire them.
The data, including the scripts to replicate results, is available here: https://osf.io/ze5cs/
Is there really class-based homophily? Evidence from a natural experiment
The data come from a natural experiment on circa 2,600 students who stayed in dormitories on Stony Brook University campus in the 2015/16 academic year. A subsample of these were randomly assigned to rooms and randomly given the chance to leave, allowing us to examine the effect of roommate characteristics (class and race) on the probability of leaving.
The data, including the scripts to replicate results, is available here: https://osf.io/6hpeb/
Code
Below I provide links to computer programming code I designed to create applications for experiments and bespoke studies.
Status discrimination on class
The experiment featured two sets of participants: the Performers and the Evaluators. The former performed a maze task and a cultural knowledge task, and the latter evaluated their performance. The application to run the experiment was coded using the Python-based Prolific platform.
The code for running the experiment is available here: https://osf.io/dexjy/
Can cognitive dissonance explain beliefs regarding meritocracy?
The experiment was based on a Dictator/Ultimatum game paradigm and featured two sets of participants: the Proposers and the Receivers. The former were radnomly given a sum of money or had to do a maths task to earn it. Then they had to offer a portion of it to a Receiver. The former were randomly given the chance to reject the Proposers' offer, and were also asked whether the offer was fair and whether the Proposer had earned the mony. The application to run the experiment was coded using the Python-based Prolific platform.
The code for running the experiment is available here: Proposer component: https://github.com/LiamOFoghlu/Proposer, Receiver component: https://github.com/LiamOFoghlu/Receiver
Hiring discrimination: the influence of referrer versus applicant gender on employer decisions
The experiment featured three sets of participants: Performers , Referrers , and Selectors . The Performers did a maths task and a childcare knowledge task, the Referrers reviewed their performance and decided whether to refer them to the Selectors, and the Selectors reviewed the referrals and decided whether to hire them. The application to run the experiment was coded using the Python-based Prolific platform.
The code for running the experiment is available here: https://github.com/LiamOFoghlu/GenderedNetworks