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and move the system toward equilibrium . Meadows ( 1999 ) normatively describes that humans create negative feedback loops as “ controls to keep important system states within safe bounds ” ( p . 9 ). Conversely , positive , or reinforcing , feedback loops xx occur when new information is inserted into a system , either through increasing complexity levels , or in the process of growth and renewal . Such positive feedback loops also disturb the sta-tus quo . Meadows ( 1999 ) notes that posi-tive feedback loops seem to say the “ more it works , the more it gains power to work some more ” ( p . 11 ). These loops are the “ sources of growth , explosion , erosion , and collapse in systems ” ( p . 11 ). Furthermore , these loops cause disequilibrium by challenging the status quo , subsequently creating a new equilibrium ( Meadows , 2008 ). Arthur ( 2013 ) argues that interaction of both positive and negative feedback loops is “ very much a defining property of complex systems ” ����� ���� Negative feedback alone reveals “ dead ” behavior and positive feedback reveals “ explosive ” behavior . Their interaction is “ interesting ” or “ complex ” behavior . By studying complex systems , scholars can reframe empirical inquiries of diversity and change ( Walby , 2003 ).
Savas ( 1970 ) connects systems to the level of municipal government ( See Figures 1-2 with system inputs and outputs ). The policy output , then , develops an iterative process in which a feedback mechanism introduces change as a new form of input ( See Bertalanffy , 1969 ). In a positive feedback loop , a preliminary change will bring further change . xxi In a negative feedback loop , an initial change will create additional change in the opposing direction , creating a homeostasis , or stable environment .
Easton and Deutsch , were early proponents of applying feedback to social theory ( Richardson , 1999 ). Easton ’ s central question is : “ what keeps a political system in power ?” ( Richardson , 1999 , p . 205 ).
Easton argued that there is a constant current of influences from the political system itself into the environment . Influences are divided between ������� and ������� . In political systems , these inputs are converted into outputs : administrative decisions , policies , political favors , and laws . These outputs answer demands and inspire support . In order to stay in power , city officials must keep demands and support in stasis with outcomes . They must keep in touch with the current state of mind of their supporters as well as the effects of previous outputs . Otherwise , the political system would fail .
We argue , feedback xxii is exhibited both top down , ( ���������� ), and bottom up ( �������� ). This complex open system is both a conscious and unconscious effort by those ���� power and those who ���� power in the system . In Stone ’ s view , ���������� in which there is dominance by groups , elites , or classes over another assumes interests are fixed . Whereas �������� , which focuses on the process and procedures of exercising power is not . The reality is that while �����������is easier to measure , it is really a non-linear process , much like �������� . Similarly , Meadows ( 2008 ) notes that when there is a dominant , or balancing loop , it has a stronger influence on behavior ( See Ford , 1999 ). And yet they are merely two sides of the same coin , two different types of feedback . ������ ���� and ������ �� by themselves are associated with what Argyris ( 1976 ) calls single-loop learning . Single-loop learning exhibits the linear , or order , paradigm . Double-loop learning acknowledges the pairing of both feedback mechanisms — two seemingly oppositional notions of power — and potentially creates a homeostasis . When this homeostasis is
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