designed to target teachers are ad hoc and imprecise, leaving DEMs with significant discretion over teacher allocation. New teachers are targeted only at district level, while within districts, DEMs are only required to target schools only with PTR above 1:60, in practice making approximately three-quarters of schools eligible to receive teachers each year.

The result is that PTR disparities largely follow the pattern of teacher preferences. The factors identified by teachers as making a school attractive as a place of work – availability of amenities at school, proximity to a trading center, and availability of amenities at the trading center – are significantly associated with lower PTRs, demonstrating that teachers are able to exercise influence to get to the school they prefer, and not necessarily to the school where they are most needed.

Political economy analysis demonstrated the informal networks through which teachers exercise influence in the system. DEMs are subject to considerable pressure from education and noneducation officials alike to game the system in favor of teachers with whom these officials have a personal relationship. At the same time, with low public awareness of the extent of PTR disparities, communities and community-level actors do not assert their power fully to retain teachers in understaffed schools. As was the case in our case study area, teachers allocated to remote schools are often able to obtain an alteration to their allocation before ever reporting to work.

Although the implementation of data-driven reforms is at an early stage, our findings and projections provide tentative support for our second proposition: that improved data, on teacher distribution and school remoteness, can contribute to the establishment of more appropriate and enforceable rules-based procedures for allocation and retention of teachers.

Our proposed categorization of schools by remoteness captures a significant degree of PTR variation, with the less remote Category C schools possessing an average PTR well below the national average and the most remote Category A schools well above average. Analysis of the 2016 allocation of new teachers in Malawi suggests that the process of consultation and discussion carried out as part of our research has already driven an observable improvement in the allocation of new teachers to schools with the greatest need.

Simulation of the potential policy applications of the categorization, through targeting of new teacher allocations and hardship allowances to the most remote schools, suggest that if fully implemented, these policies could significantly reduce PTR disparities in a short period of time. The combination of better targeting of new teachers, with the planned introduction of financial incentives for teachers working in Category A and B schools, has the potential to eliminate disparities in average category-level PTR.

Furthermore, evidence from our political economy analysis suggests that, if the categorization can be used to drive greater community awareness of PTR disparities, there is the potential for community-level actors to counteract pressure on DEMs so that DEMs are better able to resist demands to move teachers away from remote schools. Although communities and communitylevel actors appear individually as weaker voices within the network mapping, the _combined_ influence of schools, local religious leaders, TAs and Ward Councilors over DEMs was measured as on a par with that of any single more powerful actor **[Figure 5]** . This suggests that if the interests 26