13 research outputs found
Widespread Partisan Gerrymandering Mostly Cancels Nationally, but Reduces Electoral Competition
Congressional district lines in many U.S. states are drawn by partisan
actors, raising concerns about gerrymandering. To separate the partisan effects
of redistricting from the effects of other factors including geography and
redistricting rules, we compare possible party compositions of the U.S. House
under the enacted plan to those under a set of alternative simulated plans that
serve as a non-partisan baseline. We find that partisan gerrymandering is
widespread in the 2020 redistricting cycle, but most of the electoral bias it
creates cancels at the national level, giving Republicans two additional seats
on average. Geography and redistricting rules separately contribute a moderate
pro-Republican bias. Finally, we find that partisan gerrymandering reduces
electoral competition and makes the partisan composition of the U.S. House less
responsive to shifts in the national vote.Comment: 10 pages, 4 figures, plus references and appendi
Evaluating Bias and Noise Induced by the U.S. Census Bureau's Privacy Protection Methods
The United States Census Bureau faces a difficult trade-off between the
accuracy of Census statistics and the protection of individual information. We
conduct the first independent evaluation of bias and noise induced by the
Bureau's two main disclosure avoidance systems: the TopDown algorithm employed
for the 2020 Census and the swapping algorithm implemented for the 1990, 2000,
and 2010 Censuses. Our evaluation leverages the recent release of the Noisy
Measure File (NMF) as well as the availability of two independent runs of the
TopDown algorithm applied to the 2010 decennial Census. We find that the NMF
contains too much noise to be directly useful alone, especially for Hispanic
and multiracial populations. TopDown's post-processing dramatically reduces the
NMF noise and produces similarly accurate data to swapping in terms of bias and
noise. These patterns hold across census geographies with varying population
sizes and racial diversity. While the estimated errors for both TopDown and
swapping are generally no larger than other sources of Census error, they can
be relatively substantial for geographies with small total populations.Comment: 21 pages, 6 figure
Comment: The Essential Role of Policy Evaluation for the 2020 Census Disclosure Avoidance System
In "Differential Perspectives: Epistemic Disconnects Surrounding the US
Census Bureau's Use of Differential Privacy," boyd and Sarathy argue that
empirical evaluations of the Census Disclosure Avoidance System (DAS),
including our published analysis, failed to recognize how the benchmark data
against which the 2020 DAS was evaluated is never a ground truth of population
counts. In this commentary, we explain why policy evaluation, which was the
main goal of our analysis, is still meaningful without access to a perfect
ground truth. We also point out that our evaluation leveraged features specific
to the decennial Census and redistricting data, such as block-level population
invariance under swapping and voter file racial identification, better
approximating a comparison with the ground truth. Lastly, we show that accurate
statistical predictions of individual race based on the Bayesian Improved
Surname Geocoding, while not a violation of differential privacy, substantially
increases the disclosure risk of private information the Census Bureau sought
to protect. We conclude by arguing that policy makers must confront a key
trade-off between data utility and privacy protection, and an epistemic
disconnect alone is insufficient to explain disagreements between policy
choices.Comment: Version accepted to Harvard Data Science Revie
The impact of immediate breast reconstruction on the time to delivery of adjuvant therapy: the iBRA-2 study
Background:
Immediate breast reconstruction (IBR) is routinely offered to improve quality-of-life for women requiring mastectomy, but there are concerns that more complex surgery may delay adjuvant oncological treatments and compromise long-term outcomes. High-quality evidence is lacking. The iBRA-2 study aimed to investigate the impact of IBR on time to adjuvant therapy.
Methods:
Consecutive women undergoing mastectomy ± IBR for breast cancer July–December, 2016 were included. Patient demographics, operative, oncological and complication data were collected. Time from last definitive cancer surgery to first adjuvant treatment for patients undergoing mastectomy ± IBR were compared and risk factors associated with delays explored.
Results:
A total of 2540 patients were recruited from 76 centres; 1008 (39.7%) underwent IBR (implant-only [n = 675, 26.6%]; pedicled flaps [n = 105,4.1%] and free-flaps [n = 228, 8.9%]). Complications requiring re-admission or re-operation were significantly more common in patients undergoing IBR than those receiving mastectomy. Adjuvant chemotherapy or radiotherapy was required by 1235 (48.6%) patients. No clinically significant differences were seen in time to adjuvant therapy between patient groups but major complications irrespective of surgery received were significantly associated with treatment delays.
Conclusions:
IBR does not result in clinically significant delays to adjuvant therapy, but post-operative complications are associated with treatment delays. Strategies to minimise complications, including careful patient selection, are required to improve outcomes for patients