Contact
Algeria - National academic platform
...
Prepare your scientific stay

Host laboratory · Invitation letter · Application guidance

Learn more

AI & Research · arXiv Machine Learning · publications

Robustness of Refugee-Matching Gains to Off-Policy Evaluation Choices

Source excerpt

This page presents AI and research content to help researchers, students and AI tools read, cite and verify the information.

arXiv:2605.06686v1 Announce Type: new Abstract: Previous research has investigated the potential of refugee matching for boosting refugee outcomes, first considered by Bansak et al. (2018). This paper demonstrates the stability of counterfactual impact evaluation results in the context of refugee matching in the United States using a range of off-policy evaluation methods. In order to estimate counterfactual impact and test the robustness of our results, we employ several evaluation methods, including inverse probability weighting (IPW) and multiple variants of augmented inverse probability weighting (AIPW). We also consider various modifications, including alternative modeling architectures and different assignment procedures. The impact estimates remain consistent in magnitude in all scenarios as well as statistically significant in most cases. Furthermore, the estimates are also consistent with the results originally presented in Bansak et al. (2018).

Your DzCademia workshop

Assess a dataset or benchmark

A score needs data provenance, train/test separation and evaluation rules. Check licensing, coverage and possible overlap with model training data. Benchmark performance alone does not establish general capability.

A practical exercise

Choose a subset and specify what it measures. Compare methods using the same protocol and retain representative errors, not only average scores.

Record reference points
Topic
Robustness of Refugee-Matching Gains to Off-Policy Evaluation Choices
Source website
arxiv.org
Publication date at source
2026-05-11
Collection date on DzCademia
2026-05-11
My preparation plan

An indicative personal list, separate from official documents or requirements. Checkmarks stay on this device; no account needed.

0 / 5 steps checked

Read the source

DzCademia advice and exercises are separate from the source summary and requirements. This structured aid uses automated assistance and is neither scientific validation nor a selection promise. Source consulted on 2026-10-28.

View the original source

Official or original source: arXiv Machine Learning. Always check the details against the primary source.

Back to AI & Research
369
Listed events
1419485
Total visits
2191
Visits today