AJung Moon

2022

A researcher in the Science corpus: 2 papers; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom AJung Moon trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. H. Arksey
  2. Virginia Braun

Papers from AJung Moon's perspective

Ordered by how strongly the researchers AJung Moon trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
  2. Semantics derived automatically from language corpora contain human-like biases
  3. Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints
  4. Dissecting racial bias in an algorithm used to manage the health of populations
  5. Language (Technology) is Power: A Critical Survey of “Bias” in NLP
  6. Race after technology. Abolitionist tools for the new Jim Code
  7. Women also Snowboard: Overcoming Bias in Captioning Models
  8. Does Object Recognition Work for Everyone?
  9. Guidance for conducting systematic scoping reviews (International Journal of Evidence-Based Healthcare)
  10. Towards a critical race methodology in algorithmic fairness

Their papers