English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Leveraging unique insights into the special education placement processthrough written individual psychological records, I present results from thefirst ever study to examine short- and long-term returns to special educationprograms with causal machine learning and computational text analysis methods.I find that special education programs in inclusive settings have positivereturns in terms of academic performance as well as labor-market integration.Moreover, I uncover a positive effect of inclusive special education programsin comparison to segregated programs. This effect is heterogenous: segregationhas least negative effects for students with emotional or behavioral problems,and for nonnative students with special needs. Finally, I deliver optimalprogram placement rules that would maximize aggregated school performance andlabor market integration for students with special needs at lower programcosts. These placement rules would reallocate most students with special needsfrom segregation to inclusion.

Estimating returns to special education: combining machine learning and text analysis to address confounding