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Co-Designing Organizational Justice Indicators for Algorithmic Systems

Amy Voida, Fujiko Robledo Yamamoto, Nicholas Mattei, Pradeep Ragothaman, Robin Burke

Organizational justice subsumes distributional fairness and supplies concrete metrics for algorithmic recommenders.

arxiv:2605.12643 v1 · 2026-05-12 · cs.HC

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Claims

C1strongest claim

we propose organizational justice as a framework that subsumes distributional fairness as well as other normative concerns

C2weakest assumption

that the normative concerns voiced by Kiva employees in the workshops are sufficiently representative and stable to serve as the basis for generalizable metrics that the organization can use to monitor and configure its recommender system

C3one line summary

Co-design workshops at Kiva show that organizational justice better captures employee concerns for recommender systems than distributional fairness alone and yields concrete monitoring metrics.

References

40 extracted · 40 resolved · 1 Pith anchors

[1] Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, and Luiz Pizzato. 2020. Multistakeholder recommendation: Survey and research d 2020
[2] Mladen Adamovic. 2023. Organizational justice research: A review, synthesis, and research agenda.European Management Review20, 4 (2023), 762–782 2023
[3] Saleema Amershi, Maya Cakmak, William Bradley Knox, and Todd Kulesza. 2014. Power to the people: The role of humans in interactive machine learning.AI magazine35, 4 (2014), 105–120 2014
[4] 2000.Sorting things out: Classification and its consequences 2000
[5] Multisided fairness for recommendation 2017 · arXiv:1707.00093
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First computed 2026-05-18T03:09:59.969032Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

86a44cf364fb85631df4e9ab751b0a5461c53b78605f37459aa8d0bb4126ccf8

Aliases

arxiv: 2605.12643 · arxiv_version: 2605.12643v1 · doi: 10.48550/arxiv.2605.12643 · pith_short_12: Q2SEZ43E7OCW · pith_short_16: Q2SEZ43E7OCWGHPU · pith_short_8: Q2SEZ43E
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/Q2SEZ43E7OCWGHPU5GVXKGYKKR \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 86a44cf364fb85631df4e9ab751b0a5461c53b78605f37459aa8d0bb4126ccf8
Canonical record JSON
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