Lodewijk Gelauff

All Publications

• Rank, Pack, or Approve: Voting Methods in Participatory Budgeting AAAI Conference on Web and Social Media Gelauff, L. L., Goel, A. 2024

  View details for DOI 10.1609/icwsm.v18i1.31326

• Opinion Change or Differential Turnout: Changing Opinions on the Austin Police Department in a Budget Feedback Process Digital Government: Research and Practice Gelauff, L. L., Goel, A. 2024; 5 (3): 1-32

  View details for DOI 10.1145/3664822

• Fair and Inclusive Participatory Budgeting: Voter Experience with Cumulative and Quadratic Voting Interfaces Design for Equality and Justice. INTERACT 2023 Wellings, T., Banaie Heravan, F., Sharma, A., Gelauff, L., Hänggli Fricker, R., Pournaras, E. 2024

  View details for DOI 10.1007/978-3-031-61698-3_6

• ACHIEVING PARITY WITH HUMAN MODERATORS A self-moderating platform for online deliberation ROUTLEDGE HANDBOOK OF COLLECTIVE INTELLIGENCE FOR DEMOCRACY AND GOVERNANCE Gelauff, L., Nikolenko, L., Sakshuwong, S., Fishkin, J., Goel, A., Munagala, K., Siu, A., Boucher, S., Hallin, C. A., Paulson, L. 2023: 202-221

  View details for DOI 10.4324/9781003215929-15

  View details for Web of Science ID 001086105000015

• Opinion Change or Differential Turnout: Austin’s Budget Feedback Exercise and the Police Department EAAMO '22: Equity and Access in Algorithms, Mechanisms, and Optimization Gelauff, L. L., Goel, A. 2022

  View details for DOI 10.1145/3551624.3555295

• Wiki Loves Monuments: crowdsourcing the collective image of the worldwide built heritage Journal on Computing and Cultural Heritage Azizfard, N., Gelauff, L., Gransard-Desmond, J., Redi, M., Schifanella, R. 2022

  View details for DOI 10.1145/3569092

• Robust Allocations with Diversity Constraints Neural Information Processing Systems (NeurIPS) Shen, Z., Gelauff, L., Goel, A., Munagala, K. 2021
• The City of Austin FY 2022 Budget Survey Gelauff, L. L., Kim, D., Goel, A. Stanford Crowdsourced Democracy Team. Stanford. 2021

  Abstract

  This budgeting survey was collaboratively designed by the City of Austin Budget Office and the Stanford Crowdsourced Democracy Team. The purpose was to gain constructive insights into the budgeting prefer- ences of residents of Austin as input for the FY2022 budget process. It builds on a similar exercise in the previous Fiscal Year, with the difference that responses in the expenditure section are now only collected categorically, rather than with detailed budget preferences. The survey consisted of three sections: Revenue, Expenditure and Demographics. The survey was completed and submitted by 1237 respondents.

  Stanford Digital Repository
• The City of Austin FY 2021 Budget Survey Chen, Y., Gelauff, L. L., Goel, A. Stanford Crowdsourced Democracy Team. 2020

  Abstract

  This budgeting survey was collaboratively designed by the City of Austin Budget Office and the Stanford Crowdsourced Democracy Team. The purpose was to gain constructive insights into the budgeting prefer- ences of residents of Austin as input for the FY2021 budget process. The survey was first published on May 1 with an anticipated end date of May 31, and then extended due to popular demand into June. It was designed before the impact of the COVID-19 crisis became apparent, and the increased attention for the Black Lives Matter movement in May. The survey was completed and submitted by 37,006 respondents. We observe a steep increase of the number of responses on May 31, which coincided with an increased activity in the Black Lives Matter movement after the killing of George Floyd by the hands of police and calls for reducing police funding in general.

  Stanford Digital Repository
• The City of Long Beach FY 2021 Budget Exercise - Final Report Gelauff, L. L., Reamer, S. T., Goel, A. Stanford Crowdsourced Democracy Team. Stanford. 2020

  Abstract

  This budgeting exercise was designed by the Stanford Crowdsourced Democracy Team. The purpose was to both allow residents of Long Beach to gain insights in the budgeting trade-offs, and let them provide input to the City for their FY2021 budget process. The survey was first published on August 4 and responses were collected until September 4. The survey was designed in coordination with the City of Long Beach budgeting department. The City is facing a budget shortfall of about $ 30 million, and in this exercise the residents are asked to choose between various budgeting policies that would together add up to address that deficit. The survey consisted of two sections: Budget and Demographics. The exercise was presented as a ”glimpse of some of the tough choices managers have to make in balancing the City’s budget”. The exercise did not pretend to represent the City’s proposed budget or adds/cuts that are up for consideration, but rather stand-ins.

  Stanford Digital Repository
• Who Is in Your Top Three? Optimizing Learning in Elections with Many Candidates AAAI Conference on Human Computation and Crowdsourcing (HCOMP) Garg, N., Gelauff, L., Sakshuwong, S., Goel, A. 2019: 22–31
• Schrijven voor Wikipedia Gelauff, L. L. van Duuren Media. 2018
• Comparing voting methods for budget decisions on the ASSU ballot Gelauff, L. L., Sakshuwong, S., Garg, N., Goel, A. Stanford University. Stanford, CA. 2018

  Abstract

  During the 2018 Associated Students of Stanford University (ASSU; Stanford’s student body) election and annual grants process, the Stanford Crowdsourced Democracy Team (SCDT) ran a research ballot and survey to develop insights into voting behavior on the budget component of the ballot (annual grants) where multiple grant requests (hereafter: ‘projects’) are considered. We provided voters with additional voting methods for the budget component, collected further insights through a survey and demonstrated the viability of the proposed workflow.

• International comparison of technology transfer data University Technology Transfer Zwetsloot, F. J., Gelauff, L. L., Tijssen, R. J. Routledge. 2016: 428–435
• A molecular cage of nickel(II) and copper(I): a [{Ni(L)(2)}(2)(CuI)(6)] cluster resembling the active site of nickel-containing enzymes CHEMICAL COMMUNICATIONS Angamuthu, R., Gelauff, L. L., Siegler, M. A., Spek, A. L., Bouwman, E. 2009: 2700–2702

  Abstract

  A new mononuclear low-spin nickel(II) dithiolato complex, [NiL(2)] (1), reacts with copper iodide to form the hetero-octanuclear cluster [{Ni(L)(2)}(2)(CuI)(6)] (2) with four trigonal-planar CuI(2)S and two tetrahedral CuI(2)S(2) sites; anagostic interactions between the nickel(II) ions and aromatic protons have been demonstrated by variable-temperature NMR studies to pertain in solution.

  View details for DOI 10.1039/b900423h

  View details for Web of Science ID 000265890600024

  View details for PubMedID 19532926