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In the current accountability policy context, access to and use of research evidence are central to district and school improvement. Our study examines the network of relations between central office administrators and principals using a political lens to consider the ways in which the underlying politics in a district may call into question some of the assumptions around evidence use and change under accountability policy sanctions. Results indicate that relational ties regarding evidence use (data use in this case) are sparse in comparison with other work-related networks. Second, we find a misalignment between what one would expect based on district data use initiatives, formal lines of authority, and communication patterns and the underlying informal social interactions of the leaders around the use of data. We discuss the implications of this research for district improvement and the use of evidence in the current policy context.

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When interest groups compete to influence legislators, the resulting legislation is often vague, and thus obliges the groups to continue their fight in the executive. On its face, this seems inefficient-at least from the point of view of the groups. We explore this intuition in a model of "nested lobbying" in which interest groups first compete to influence a legislative agenda setter, then compete to influence legislative votes over the resulting agenda. If the resulting legislation grants discretion to the executive, the final prize is allocated in yet one more contest in the bureaucracy. We find that when the status quo is non-discretionary, competition over the agenda never results in an agenda that includes discretion. Surprisingly, however, a discretionary status quo can stand with probability 1 if the preferences of the bureaucracy, the legislature, and the agenda setter are arranged in an "iron triangle". Specifically, the bureaucracy and agenda setter must be biased in favor of one group, while the legislature is biased in favor of the other.

<p>Canada is a signatory to the Global Methane Pledge and is aiming to achieve a 75% cut in methane from 2030 levels from oil and gas production through regulatory updates and a 50% cut in waste sector emissions using new regulations. Despite numerous large-scale studies that have measured and identified emission sources from Canada's oil and gas sector, there are virtually no measurements of emissions from landfills in Canada. As such, inventory values for landfill emissions are based on a combination of industry-submitted data and emission factors. Canada could design better policies and regulations if policymakers had access to actual emission rates and source types. Therefore, we designed and carried out a large-scale measurement campaign targeting minimally 125 landfills across Canada, using aircraft mass balance measurements and truck-based measurements (i.e., downwind and onsite transects) coupled with Gaussian inversions to determine emission rate. This study focuses on methodologies used to determine source locations, or methane hotspots, on the landfill surface. In Particular, source attribution methods included a Lagrangian back trajectory footprint analysis of mobile surveys, onsite mixing ratios and winds measured with the truck, as well as Landsat thermal retrievals that have been shown in prior studies to correlate with methane hotspots. Measurements were carried out between June and December 2022 using one or more measurement methodologies for a total of 143 sites. We performed truck-based measurements of mixing ratios across navigable portions of 59 landfills. All indicators showed some correlation to mixing ratios collected onsite, although Lagrangian analysis products from downwind measurements were somewhat more reliable in flagging hotspots than the satellite thermal indices. The indicators often highlighted the active disposal face, leachate impoundment ponds, or compost areas, as the active source area. This study will help contribute much-needed source information for solid waste sector regulatory design in Canada and has the potential to help improve models of landfill methane generation.</p>