The present research investigated Lerner's (1970, 1980) just‐world theory by manipulating victim‐related factors in a scenario and measuring several possible strategies for dealing with the threat to participants' just‐world beliefs created by the victim's intense suffering. Participants read a story about a victim who varied in terms of his character (likeable vs. unlikeable) and behavioral responsibility for causing his accident (high vs. low). The general pattern of results showed that for the unlikeable low‐responsibility victim, the primary response to protect justice beliefs appeared to be character derogation; for the likeable high‐responsibility victim, the primary protective strategy appeared to be blame; and for the likeable low‐responsibility victim, the primary protective strategy appeared to be compensation. Implications for just‐world theory are discussed.
Journal of Applied Social Psychology – Wiley
Published: Mar 1, 2006
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera