Explaining fragmented and fluid mobilization in gold mining concessions in eastern Democratic Republic of the Congo

The expansion of industrial mining in the eastern Democratic Republic of the Congo has sparked social mobilization in gold mining concessions, most of which are important sites for artisanal mining. Congruent with observations on the nature of social movements in Africa, such mobilization is hyper-fragmented and fluid. We ascribe this high degree of fluidity and fragmentation both to factors internal to the social mobilization effort, including limited organizational potential and the heterogeneity of attitudes and discourses, and the political and socio-economic context, characterized by intense conflicts, patronage-based politics, poverty and repression. Additionally, we identify certain company practices as undermining the sustainability and coherence of social mobilization, in particular: the co-optation of intermediaries and protestors, acquiescence in practices of favoritism, fostering a repressive climate, and token commitment to community participation. We conclude that to understand social mobilization in mining concessions, it is important to study the interplay between political (re)actions ‘from above’ and ‘from below’, and to recognize the diversity of these (re)actions, which are located on a wide spectrum between resistance and repression on the one hand, and collaboration and co-optation on the other

Patient satisfaction with health care at a tertiary hospital in Northern Malawi: results from a triangulated cross-sectional study

Abstract Background In 2016 the Malawi government embarked on several interrelated health sector reforms aimed at improving the quality of health services at all levels of care and attain Universal Health Coverage by 2030. Patient satisfaction with services is an important proxy measure of quality. We assessed patient satisfaction at a tertiary hospital in Northern Malawi to understand the current state. Methods We conducted exit interviews with patients aged ≥ 18 years using a 28 statement interviewer administered questionnaire. Patients were asked to express their level of agreement to each statement on a five-point Likert scale – strongly disagree to strongly agree, corresponding to scores of 1 to 5. Overall patient satisfaction was calculated by summing up the scores and dividing the sum by the number of statements. Mean score &gt; 3 constituted satisfaction while mean score ≤ 3 constituted dissatisfaction. A χ2 test was used to assess the association between overall patient satisfaction and demographic variables, visit type and clinic consulted at alpha 0.05. Patient self-rated satisfaction was determined from a single statement that asked patients to rate their satisfaction with services on a five-point Likert scale. We also asked patients to mention aspects of hospital care that they did not like. Responses were summarized into major issues which are presented according to frequencies. Results Overall patient satisfaction was 8.4% (95% CI: 5.2 − 12.9%). Self-rated patient satisfaction was 8.9% (95% CI: 5.5 − 13.4%). There was no significant association between overall patient satisfaction and all predictor variables assessed. Patients raised six major issues that dampened their health care seeking experience, including health workers reporting late to work, doctors not listening to patients concerns and neither examining them properly nor explaining the diagnosis, shortage of medicines, diagnostics and medical equipment, unprofessional conduct of health workers, poor sanitation and cleanliness, and health worker behaviour of favouring relatives and friends over other patients. Conclusions We found very low levels of patient satisfaction, suggesting that quality of services in the public health sector is still poor. It is, therefore, critical to accelerate and innovate the Ministry of Health’s quality improvement initiatives to attain Malawi’s health goals. </jats:sec

mmrefpoints: Projecting long-term marine mammal abundance with bycatch

An R package that generates marine mammal population projections based on starting abundance, life history, and bycatch rates, based on the BALEEN II population dynamics model