| Transparent to whom? No algorithmic accountability without a critical audience J Kemper, D Kolkman Information, Communication & Society 14 (1), 2081-2096, 2018 | 299 | 2018 |
| The usefulness of algorithmic models in policy making D Kolkman Government Information Quarterly 37 (3), 2020 | 78 | 2020 |
| The (in) credibility of algorithmic models to non-experts D Kolkman Information, Communication & Society 25 (1), 93-109, 2022 | 48 | 2022 |
| How to build models for government: Criteria driving model acceptance in policymaking DA Kolkman, P Campo, T Balke-Visser, N Gilbert Policy Sciences 49, 489-504, 2016 | 44 | 2016 |
| Is firm growth random? A machine learning perspective A van Witteloostuijn, D Kolkman Journal of Business Venturing Insights 11 (1), 1-5, 2019 | 37 | 2019 |
| F** k the algorithm?: what the world can learn from the UK’s A-level grading fiasco D Kolkman Impact of Social Sciences Blog, 2020 | 26 | 2020 |
| Data Science in Strategy Machine learning and text analysis in the study of firm growth D Kolkman, A van Witteloostuijn Tinbergen Institute Discussion Paper, 2018 | 11 | 2018 |
| Justitia ex machina: The impact of an AI system on legal decision-making and discretionary authority D Kolkman, F Bex, N Narayan, M van der Put Big Data & Society 11 (2), 20539517241255101, 2024 | 4 | 2024 |
| Challenges in Data Science Projects with SMEs: An Analysis and Decision Support Tool D Kolkman, R Sneep Available at SSRN 3343092, 2019 | 3 | 2019 |
| Glitch Studies and the Ambiguous Objectivity of Algorithms D Kolkman, J Kemper SSRN, 2017 | 3 | 2017 |
| Clearer Governmental Communication: Text Simplification with ChatGPT Evaluated by Quantitative and Qualitative Research NB van Raaij, D Kolkman, K Podoynitsyna Proceedings of the Workshop on DeTermIt! Evaluating Text Difficulty in a …, 2024 | 1 | 2024 |
| Is public accountability possible in algorithmic policymaking? The case for a public watchdog D Kolkman Impact of Social Sciences Blog, 2020 | 1 | 2020 |
| Complex adaptive systems and the new mobilities paradigm DA Kolkman | 1 | 2012 |
| AI decision making doesn’t need to be explainable, but it should be responsive D Kolkman, G van Maanen LSE Impact Blog, 2025 | | 2025 |
| Algorithmic models through a representational lens D Kolkman, G van Maanen The Information Society 41 (1), 33-50, 2025 | | 2025 |
| Data science and automation in the process of theorizing: Machine learning’s power of induction in the co-duction cycle D Kolkman, GK Lee, A van Witteloostuijn PloS one 19 (11), e0309318, 2024 | | 2024 |
| Factors enabling and constraining higher levels of data maturity among SMEs W Liebregts, D Kolkman Research Handbook on Self-Employment and Public Policy, 395-416, 2024 | | 2024 |
| Algorithmic models through a representational lens G van Maanen, D Kolkman The Information Society, 2024 | | 2024 |
| You Will Be Assimilated: Reflections on Ethnographic Fieldwork on Algorithmic Systems D Kolkman Collaborative Researchin the Datafied Society, 235, 2024 | | 2024 |
| The Elementary Scenario Component Metric for Summarization Evaluation M Kirilov, D Kolkman, BJ Butijn Proceedings of the 5th International Conference on Natural Language and …, 2022 | | 2022 |
Jakko KemperAssistant Professor in Digital Aesthetics and Platform Vernaculars, University of AmsterdamVerified email at uva.nl