I discuss two categories of causal relationships: primitive causal interactions of the sort characterized by Phil Dowe and the more general manipulable causal relationships as defined by James Woodward. All primitive causal interactions are manipulable causal relationships, but there are manipulable causal relationships that are not primitive causal interactions. I’ll call the latter constructed causal relationships, and I’ll argue that constructed causal relationships serve as a foundation for both computing and complex systems. -/- Perhaps even more interesting are autonomous causal relationships. These are constructed causal relationships in which the causal mechanism resides primarily in the effect. A typical example is a software execution engine. Software execution engines are on the effect side of a cause-effect relationship in which software is the cause and the behavior of the execution engine is the effect. The mechanism responsible for that causal relationship resides in the execution engine.

Philosophy

Causality, computing, and complexity

1 Causality, computing, and complexity Russ Abbott Department of Computer Science California State University, Los Angeles Abstract. I discuss two categories of causal relationships: primitive causal interactions of the sort characterized by Phil Dowe and the more general manipulable causal relationships as defined by James Woodward. All primitive causal interactions are manipulable causal relationships, but there are manipulable causal relationships that are not primitive causal interactions. I'll call the latter constructed causal relationships, and I'll argue that constructed causal relationships serve as a foundation for both computing and complex systems. Perhaps even more interesting are autonomous causal relationships. These are constructed causal relationships in which the causal mechanism resides primarily in the effect. A typical example is a software execution engine. Software execution engines are on the effect side of a cause-effect relationship in which software is the cause and the behavior of the execution engine is the effect. The mechanism responsible for that causal relationship resides in the execution engine. Introduction Causality has been a longstanding and controversial topic in philosophy. I think it's fair to say, though, that Phil Dowe's primitive causal interactions and James Woodward's manipulable causality currently reign as the primary ways to think about philosophical causality. See the section below on actions and events for some additional discussion. Primitive causal interactions Primitive causal interactions correspond to direct interactions-the sorts of interactions one associates with billiard balls hitting one another. (Dowe 2000) defines a [primitive1] causal interaction as follows. An object is anything found in the ontology of science (such as particles, waves or fields), or common sense (such as chairs, buildings, or people). A world line is the collection of points on a space-time (Minkowski) diagram which represents the history of an object. A causal interaction is an intersection of world lines which involves [an] exchange of a conserved quantity. For our purposes one can think of a primitive causal interaction as occurring at a single moment in time and at a single point in space.2 Manipulable causal relationships A manipulable causal relationship is defined by Woodward (2003, 2012/forthcoming), as follows.3 1 Dowe uses the term causal interaction rather than primitive causal interaction. He entitles his book Physical Causality reflecting his commitment to fundamental physical interactions. Hence my use of the term primitive. 2 Quantum interactions do not occur at a single moment in time or at a single point in space. They occur through an exchange of virtual particles. Emission and absorption occur at different moments and different locations. But this issue will not be relevant for this paper, which will be concerned with macro-level interactions. 3 Woodward's general definition is expressed in terms of probability distributions rather than just values. 2 2 X causes Y iff (i) there is a possible intervention4 that changes the value of X which is such that (ii) under this intervention the value of Y changes. The motto characterizing manipulable causal relationships is: when you wiggle X, Y wiggles. The idea is that X provides access to Y for the purpose of change. The more common term for Woodward-style causality is interventionist causality. I am using the term manipulable instead because it seems to reflect Woodward's intent more accurately. Woodward (2012/forthcoming) says that his approach serves our human desire to manipulate in the world. "Even if one wants to consign the notion of cause to the rubbish heap, one needs some way [to identify] relationships [that can be exploited] for manipulation and control."5 Philosophical causality can be a hall of mirrors Consider the following example: Bob killed the plant by not watering it. No conserved quantity is transferred between Bob and the plant. Yet from a manipulability perspective Bob's not watering the plant caused it to die. (We are assuming that it was Bob's practice to water the plant.) Changing Bob's behavior from watering the plant to not watering the plant changed the plant's fate from living to dying. So Bob's killing the plant by not watering it is a manipulable causal relationship that is not a primitive causal interaction. One can construct arbitrarily complex-and perhaps arbitrarily foolish and arbitrarily vexing-examples. What if Alice, noticing that Bob was no longer watering the plant, did so herself, thereby keeping it alive? Did Bob's not watering the plant cause it to stay alive-because his not watering it caused Alice to water it, which caused it to stay alive? I do not intend to be drawn into issues of this sort. See Paul and Hall (2012) for an extended discussion of examples like this. Constructed causal relationships I'll use the term constructed causal relationships for a manipulable causal relationship that is not a primitive causal interaction. Bob's killing the plant (or not killing the plant depending on whether Alice takes over the job) by not watering it are two examples. For another, consider a light switch or a water faucet. What happens when one turns the switch or faucet from Off to On? First of all, light starts shining or water starts flowing. And this happens so reliably that it makes sense to say that manipulable causal relationships exist between the position of the switch/faucet and the flowing or not flowing of the light/water.6 What role do actions and events play in manipulable causal relationships? When thinking about causal relationships it's important not to rely too heavily on the intuitive meaning of the verb to cause. One common understanding of to cause is to make happen: "X causes Y" is often taken to mean that X makes Y happen or X brings Y about. To cause is an active transitive verb: a subject does something to an object. To a great extent this is what the conserved-quantity-transfer notion of cause captures. Transferring a conserved quantity to or from an object typically makes something happen to that object. In particular the cause and the effect are both events. (This is the position that Paul and Hall take.) Schaeffer (2014) puts it this way. 4 An "intervention" is an idealized unconfounded manipulation of X that changes Y, if at all, only through X. 5 Although Woodward's approach may be motivated by a human goal of manipulation, it is not a commitment to a causality dependent on human manipulations. An intervention simply requires that something change, not that a human being change it. See, for example, (Woodward 2013, section 9) for a discussion. 6 More precisely and as discussed in the next section, the relationship between the position of the switch/faucet and the flow of light/water is persistent under the Off/On intervention in just those situations in which (perhaps somewhat circularly) the intervention results in water/light flowing or not. 3 3 The standard view of the causal relata is that they are of the category of event, and that their number is two, in the roles of cause and effect. So on the standard view, when the cue ball knocks the nine ball into the corner pocket, there is said to be an (actual) event e1 of the cue ball striking the nine ball, and an (actual, distinct) event e2 of the nine ball sinking into the corner pocket, such that e1 is cause and e2 effect. ... The standard view has, of course, been disputed on all counts. As to category, while the standard view casts the causal relata as events, one also finds considerable support for facts, and occasional support for such other entities as features, tropes, states of affairs, situations, and aspects. Allegiances are further complicated by disagreements over what events, facts, and these other creatures are. In the perspective taken here a manipulable causal relationship need not involve either an action or an event. Recall that for Woodward a manipulable causal relationship exists between X and Y (to simply somewhat) if changing X-i.e., intervening on X-results in a consistent change to Y. But X and Y themselves need not be actions or events. They can be static properties. All that is required is that the value(s) for Y must be determined for any given value(s) for X.7 A more straightforward way to put this is that a manipulable causal relationship is a functional dependency as defined in relational database theory.8 For example, in US addresses there is a manipulable causal relationship between ZIP code and state.9 Given a ZIP code, the state is determined. Furthermore, the ZIP code → state dependency is invariant under an intervention that changes ZIP code from one value to another. • If in a database system, one changes a person's ZIP code, then that person's state also changes-and in a manner consistent with other ZIP codes. • If an attempt is made to enter data showing two people with the same ZIP code but different states the system rejects that data. Another way to think about a manipulable causal relationship between X and Y is as if X were a remote control for Y: one can change Y by changing X. Although a nice metaphor and not a bad thought aid, this metaphor is misleading since most remote controls are linked to their controlled devices via a physical signal. As our database example shows no such direct physical link need necessarily exist. Woodward refers to the link between cause and effect as a generalization that is invariant under an intervention. Suppose there is a function f relating values of X to values of Y: Y = f(X). This relation is invariant under intervention I if and only if were X set through intervention I to some value x0, Y would then have the value f(x0).10 Woodward is careful not to require that the function f hold for every change to X. In this way he distinguishes a law of nature from a more limited generalization that holds under certain but not all conditions. For example, in our ZIP code example, it's possible that one may know a person's state but not a person's ZIP code. Furthermore there may be multiple people with unknown ZIP codes-each 7 X and Y may be collections of properties. 8 Wikipedia/Functional dependency has a good explanation. 9 This isn't a law of nature; it just happens to be the way ZIP codes are assigned. No ZIP code crosses a state border; every ZIP code is completely contained within some state. 10 I have been unable to find a clear direct statement by Woodward. The preceding was paraphrased from Hiddleston 2005. 4 4 residing in a different state. Setting the ZIP code for these people to unknown does not guarantee that they all have the same value for state. The only intervention under which the ZIP code → state dependency holds is one that sets ZIP code to some valid11 value. Causal mechanisms Earlier we said that manipulable causal relationships don't necessarily involve specific causal mechanisms. But they aren't magic either. For any manipulable causal relationship there must be some means whereby the dependency between cause and effect is maintained. For example, suppose you take a picture of yourself in a mirror, i.e., a selfie. There is a manipulable causal relationship between the visual presentation projected toward the mirror, the cause, and the image captured by the camera, the effect. Change, i.e., manipulate, your expression, and the captured image will change. The mirror provides a significant part of the causal mechanism linking cause to effect. Let's return to our switch example. What happens when we turn the switch from Off to On? The key to most constructed causal relationships is that a change to the cause changes the environment in such a way that the effect occurs. For example, flipping a light switch closes a circuit so that under normal circumstances-in which a voltage is available in the circuit, the rest of the circuit is unbroken, the light bulb is working properly, etc.-the light bulb produces light. A change to the cause results in a change to the effect even though the change to the cause does not transfer a conserved quantity to the effect: the kinetic energy involved in closing the switch was not transferred to the light bulb. An even simpler story applies to a water faucet. Turning it to On allows water to flow through the tap. On its own, turning the faucet to On does nothing to push water through the tap. But water flows through the tap only when the system has water and sufficient pressure. In addition, there must not be either a hole or a blockage in the pipe between the faucet and the tap. Furthermore, the pipe must not be made of sugar, which will dissolve as water flows through it. Similarly with the mirror example. The cause and the effect are in a manipulable causal relationship only if there is a source of light, the camera is working, there is room on the camera's memory card, nothing blocks the flow of light from cause to effect, etc. As these examples illustrate one can multiply almost endlessly conditions that must hold for an effect to occur in a constructed causal relationship. They also suggest a motivation for using the term constructed for these types of causal relationships. Such relationships depend on mechanisms in the environment. An electric switch lever, a faucet knob, and a mirror do nothing unless embedded within a larger construction. 11 According to the United States Postal Service there are somewhat more than 42,000 ZIP codes. Since there are 100,000 five-digits strings, fewer than half of all five-digit strings are valid ZIP codes. battery switch switch bulb bulb battery 5 5 Cause-and-effect in software Software is text-or when compiled some other static representation of information. On its own software does nothing. For software to have any dynamic properties it must be executed by a software execution engine. Let's compare a software execution engine to a Rube Goldberg machine such as the Self-Operating Napkin12 shown above. The two differ in two important ways. 1. A software execution engine follows directions encoded symbolically. A Rube Goldberg machine consists of a series of primitive causal interactions. There are no symbolic instructions. 2. A software execution engine runs on an independent energy supply-usually electricity from an external source. A Rube Goldberg machine is powered by multiple integrated sources of energy-usually the conversion of gravitational potential energy into kinetic energy although sometimes energy released through the action of living organisms or chemical energy as in combustion. The charm of a Rube Goldberg machine inheres in the mechanisms through which the release of energy from one source triggers the release of energy from the next. Without this cascading sequence of energy releases the machine would stop. Energetics, a primary concern for Rube Goldberg machines, is irrelevant in software execution engines. What are the causal relationships in software? Software is in a constructed causal relationship with its execution engine. The software is the cause; the actions of the engine are the effects. Software execution is something like a railroad train moving along its track-or multiple tracks if the software is multiply threaded. The software is the track; the execution engine is the train. Changing the software results in a change in the behavior of the execution engine. In many ways the cause and effect relationship between software and its execution engine resembles the way Laplace used the terms cause and effect when describing his demon. "We may regard the present state of the universe as the effect of its past and the cause of its future." [Emphasis added]13 12 The Self-Operating Napkin is activated when soup spoon (A) is raised to mouth, pulling string (B) and thereby jerking ladle (C), which throws cracker (D) past parrot (E). Parrot jumps after cracker and perch (F) tilts, upsetting seeds (G) into pail (H). Extra weight in pail pulls cord (I), which opens and lights automatic cigar lighter (J), setting off skyrocket (K) which causes sickle (L) to cut string (M) and allow pendulum with attached napkin to swing back and forth, thereby wiping chin. (From Wikipedia 2015.) 13 The rest of the description is as follows. "An intellect which at a certain moment would know all forces that set nature in motion, and all positions of all items of which nature is composed, if this intellect were also vast enough to submit these data to analysis, it would embrace in a single formula the movements of the greatest 6 6 In using the terms cause and effect Laplace was not intending to add anything to physics. All he was saying is that the laws of physics (as understood at the time14) were sufficient to enable one to see the world in terms of cause and effect. Laplace didn't say explicitly how cause and effect are related to the laws of physics. Dowe's primitive causal interaction is an attempt to make the means of mapping the laws of physics onto the terms cause and effect more precise. Aaronson (2014) recently made a point similar to that of Laplace. The laws of physics aren't "suggestions," which particles obey when they feel like it but ignore when Uri Geller picks up a spoon.15 ... The world "obeys" them in much the same sense that a computer obeys its code. Hoefer (2015) characterizes this way of thinking as follows. The laws of nature are assumed to be pushy explainers. They make things happen in certain ways. [The laws of nature] are implicitly thought of as the cause of everything that happens. Hoefer goes on to deprecate this way of thinking-as if nature could be distinguished from her laws. Talk of laws "governing" ... is so commonplace that it takes an effort of will to see it as metaphorical. In contrast, in a world in which a software execution engine is running some software there are as Aaronson suggests two distinct things: the software and the execution engine. The software plays the role of pushy laws of nature-and hence is the cause of everything that happens. The execution engine plays the role of the material world, which "obeys" those laws. The software governs the engine; there is no metaphor. As indicated above, though, there are fundamental differences. • The laws of nature are neither expressed symbolically nor executed by physical objects. The laws of nature are not distinct from nature itself. It is only metaphorically that the laws of nature direct the behavior of material objects. In contrast software is distinct from an execution engine. It makes sense to say that software directs the behavior of the engine. • The physical world needs a source of energy if it is to "obey" the laws. More accurately, the laws of nature have built into them energetic requirements. That is not the case with a software execution engine. A software execution engine is assumed to be self-powered. Within a software-governed world, its energy source is not relevant. Software need not be concerned about whether the execution engine has sufficient energy to run. Autonomous causal mechanisms If software is the cause of the behavior of its software execution engine, what is the causal mechanism? The answer, of course, is that software execution engines are built to interpret software instructions. In bodies of the universe and those of the tiniest atom; for such an intellect nothing would be uncertain and the future just like the past would be present before its eyes." 14 We now know that Laplace was incorrect on at least three counts. (i) Quantum randomness make prediction impossible. Laplace could be forgiven for this mistake since he did not know about quantum mechanics. (ii) Chaos makes prediction impossible. We now know that it's impossible (a) to know the forces and positions of nature with sufficient precision and then (b) computationally to propagate those forces and positions in a way that retains that level of precision over an extended time span to achieve Laplace's intended result. Laplace was not aware of chaos theory either. (iii) Biological evolution depends on (random) mutation and recombination. Laplace did not know about evolution, and had he known it's not clear what role he would have assigned to randomness in mutation and recombination. Had he assumed they are truly random, he would have known that prediction is not possible. Had he assumed that there is a non-random mechanism behind them-such as chaotic or quantum phenomena-he would have been stuck with the problems of (i) and (ii). 15 Uri Geller is a stage magician who "bends" spoons as part of his act. See, for example, (Randi 2006). 7 7 an inversion of the usual causal mechanism relationship-in which a cause produces an effect- software execution engines make themselves the effect of the software that serves as the cause. The cause-effect relationship still holds: the software is the cause; the behavior of the execution engine is the effect. It's just that the mechanism is backward. Instead of projecting cause to effect, the engine, whose behavior is the effect, maps the cause onto whatever effect it determines. Because the effect engine serves as the causal mechanism, I'll refer to this (perhaps paradoxically) as autonomous causality and to the effect as an autonomous effect. Anything capable of following symbolic instructions illustrates autonomous causality. Besides software execution engines, examples include human beings when acting as drivers obeying traffic signals and as soldiers following orders. Many entities that serve as autonomous effects can be programmed to provide effect components for multiple causal relationships. Examples include human beings, computers, trainable animals, and now robots. Because they can be programmed to provide the effect component for many different causal relationships, such entities are generally considered valuable resources. Review Let's review what we've said about causal relationships. • We are considering two kinds of causal relationships. o Primitive causal interactions are based on an exchange of a conserved quantity. o Manipulable causal relationships reflect situations in which an effect can be manipulated via some intervention on the cause. The cause acts as something like a remote control for the effect. • A manipulable causal relationship is formally equivalent to a functional dependency. As is the case with functional dependencies, manipulable causal relationships may connect sets of static properties as cause and effect. • Neither the cause nor the effect of a manipulable causal relationship need be either an event or an action. • All primitive causal interactions are manipulable causal relationships but not vice versa. • I am calling manipulable causal relationships that are not primitive causal interactions constructed causal relationships. • For every manipulable causal relationship, even those that connect static sets of properties, it is possible to identify some causal mechanism that brings about the causal relationship. There appear to be (at least) the following categories of causal mechanisms. o The causal mechanism may be a cascade of primitive causal interactions that begin at the cause and propagate to the effect thereby projecting changes in the cause onto changes to the effect. Think of a row of dominoes knocking each other over, the gears of a clock, a Rube Goldberg machine, chemical combustion, a nuclear reaction, or mechanisms that maintain homeostatic conditions such as a thermostat. o The causal mechanism may exist in the environment-and only under certain conditions-as in the example of an electric switch, a water faucet, or a mirror. o The causal mechanism may be built into the framework within which the relationship exists-as in the example of a functional dependency linking ZIP code to state. o the causal mechanism may be built into the effect-as in a software execution engine. I am calling this form of causality autonomous causality. 8 8 The Switch The final major bullet in the preceding section tells us that for every causal relationship some mechanism (broadly understood16) links the cause to the effect. I'll use the term Switch for any causal mechanism not involving the exchange of a conserved quantity. A Switch: a means or mechanism whereby a cause is linked to an effect in such a way that a change to the cause results in a consistent change to the effect without the exchange of a conserved quantity. Even though a Switch is intended to represent a physical realization of a constructed causal relationship, it is defined quite abstractly. • In software terms, a Switch is polymorphic: the types of the values to be assigned to the cause and effect are not specified. • Switch functionality is expressed abstractly: that a change to the cause results in a consistent change to the effect. But the specific change, e.g., the function that maps cause to effect and the mechanism that realizes that mapping are left open. These properties are left to the concrete realization of a Switch in any particular case. • Switches tend to lack of proportionality. They often have the property known as non-linearity: the magnitude of the change in the cause generally has little or no relationship to the magnitude of the change in the effect. This is not the case for primitive causal interactions. Since these depend on an exchange of a conserved quantity, the magnitude of the change in the cause is linked directly to the magnitude of the change in the effect. A Switch is a generic mechanisms for building manipulable causal relationships. In software terms a Switch is something like an abstract class; it can be understood as having an abstract method that maps cause values to effect values. To create a concrete manipulable causal relationship one (a) creates a non-abstract Switch subclass with a specific cause and effect and (b) builds a concrete implementation of the cause-to-effect mapping. As we'll see, switches are fundamental to both computing and complex systems. I'll use the term autonomous Switch for the switch component of an autonomous causal relationship. The Turing machine is an autonomous Switch Earlier we discussed how the causal mechanism that links software to its execution engine resides in the execution engine. A software execution engine is able to follow instructions expressed symbolically: it reads software and does what the software instructs it to do. This is fundamentally different from most other causal mechanisms. We referred to this as autonomous causality. In this section I want to look at a Turing machine, which I will claim is an autonomous Switch. A Turing machine is assumed to be in one of a finite number of pre-specified internal states. It is assumed to have a read/write head, which is positioned over a symbol from a finite alphabet-also fixed in advance-arranged in a finite but unbounded sequence. 17 As befits its name, the read/write head can 16 Online definitions of mechanism include the following. • a process or system used to produce a particular result (Merriam-Webster) • the agency or means by which an effect is produced (Dictionary.com and FreeDictionary.com) • a natural or established process by which something takes place or is brought about (Google.com and Oxford) • the technical aspects of doing something (Wordnet.com, Wordnet.dk, and vocabulary.com) See also the definitions at Onelook.com. 17 The unboundedness of the symbol sequence does not affect the step-by-step operations the machine is assumed capable of performing. At each step the device reads a symbol and then acts as described. 9 9 read the symbol over which it is positioned. Based on its current state and the symbol it reads, the machine (a) writes a replacement symbol (perhaps the same as the original), (b) either does not move the read/write head or moves the read/write head left or right, and (c) either changes its internal state to some different state or remains in the same internal state. Turing machines are frequently represented as collections of 5-tuples-often written as rules. (<statepre>, <symbolpre>) → (<statepost>, <symbolpost>, <move>) The <state> and <symbol> components are the values for the machine's internal state and the symbol being read/written before and after the rule is applied. The <move> value is one of {left, right, no-move}. Following Woodward (2003) and Pearl (2009) cause and effect can be represented by variables that assume values from predefined domains. It will often be useful to think of these values as n-tuples. So a cause may have values C = (c1, c2, ..., cn), and an effect may have values E = (e1, e2, ..., em). Modifying the cause from Ca to Cb results in a modification to the effect from Ea to Eb. Given this convention a Turing machine is an abstract Switch: the Cause value is a (<state>, <symbol>) pair; the Effect value is a (<state>, <symbol>, <move>) triple. A Turing machine is an abstract Switch because Turing offered no physical instructions for building his machines. All we can say is that the computational capability of a Turing machine is essentially that of a Switch. Turing machines are autonomous in that they provide the mechanism that links the cause to the effect. So Turing machines are autonomous Switches. In other words we can reframe the notion of a Turing machine as an autonomous Switch plus unbounded storage. Causality and functionality Most software has either a user manual or a functional specification (or both). Either one describes what's known as the software's functionality, i.e., what the software does when executed-assuming that what the software does when executed conforms to its manual or specification. Like a Turing machine, executing software implements an autonomous causal relationship: it's state/input is the cause; its behavior/output is the effect. The executing software itself provides the causal mechanism. Notwithstanding the unremarkable place the notion of functionality holds in computer science, that same notion seems to raise difficulties for the philosophy of biology. In that context, functionality is typically understood in terms of the role a function plays in the larger context of an organism. For example, one may say that the function of the heart is to pump blood and note that the pumping of blood is necessary for the survival of the organism. When understood in those terms, the heart is implicitly assumed to have a purpose, to do its part in the overall design of the organism. But philosophers object that design and teleology have no place in modern science. Nature doesn't design; nature doesn't operate in terms of purposes. One way around this problem is known as naturalizing functionality. The function exists because it was selected by evolution as one of the mechanisms that resulted in the survival of the organism. From this perspective one would say that the function of the heart is to pump blood, but one wouldn't say that the function of the heart is to produce a semi-regular rhythmic beating sound-even though the heart does both. From a causality perspective, the heart provides a causal mechanism that links various physiological states to both the circulation of blood and the generation of a beating sound. It seems to me that this is a simpler way of looking at it. Beating noises are a causal effect whether or not they are required for survival. So when speaking of functionality I will be referring to causal effects rather than to biological needs. 10 10 Causality and complex systems Steven Weinberg is a committed reductionist. He adopts (1995) a position he calls grand reductionism. All of nature is the way it is (with certain qualifications about initial conditions and historical accidents) because of simple universal laws, to which all other scientific laws may in some sense be reduced. Note how Weinberg brackets off "initial conditions and historical accidents." According to many biologists, much of biology is due to historical accidents and hence would not fall within Weinberg's grand reductionism perspective. As we will see, complex systems are built on the constructed causal relationships of historical accidents. I want to examine two examples. The gene scwitch Jacob and Monod (1961) won the Nobel prize for their discovery of what has come to be known as the gene switch. E. coli is capable of digesting lactose. To do so it produces an enzyme that helps in the digestion. But production of that enzyme uses cellular resources. Therefore it makes sense to produce the enzyme only when lactose is present. To accomplish this, E. coli produces a protein-known as a repressor-that binds to DNA just "upstream" of the genes for the lactose enzyme. The repressor protein blocks transcription of the enzyme genes. But when lactose is present, a lactose derivative binds to the repressor pulling it off the DNA. This unblocks transcription, resulting in the production of the enzyme. This is a Switch. The presence or absence of lactose is the cause; production of the lactose enzyme is the effect. Although the preceding sketches the essential causal process, as with most things in biology, the actual mechanism is more complex. Since Jacob and Monod's discovery, many examples of gene regulation processes have been observed. Savageau (2012) describes the situation like this. The rich variety of mechanisms governing gene expression is the result of historical accident. Why are there positive and negative regulators? God only knows. There is no design-what works, works; what doesn't is dead. The only rule is that there are no rules. Plant defense against herbivores As a second example consider how plants respond to herbivores. (Paraphrased from War et. al., 2012) Plants confront herbivores both directly-by producing specialized morphological structures or secondary metabolites and proteins that have toxic, repellent, and/or anti-nutritional effects on the herbivores-and indirectly. Indirect defenses are mediated by the release of a blend of Herbivore Induced Plant Volatiles (HIPVs) that attract natural enemies of the herbivores. For example, mechanically wounded cabbage leaves emit volatiles that attract parasitic wasps which prey on the herbivores. What I find especially worth noting is the combination of historical accident and causality. Through an extended process of co-evolution-more than 1/3 billion years-plants and the enemies of the plant's enemies have "agreed" on signaling compounds. The particular chemicals don't matter. All that matters is (a) that the chemical can be produced and emitted by the plant, (b) that it can be carried by air currents, and (c) that herbivore predators can evolve to respond to the chemical as an attractant. In causal terms, the attack of a herbivore is linked as a cause via a complex causal mechanism to an effect, which is a counter attack by a herbivore predator. In other words, the plant has turned an attack into a cause that produces a counter-attack effect. Such networks of contingently constructed causal relationships are typical of complex systems-which is one reason they are considered complex! 11 11 Bricolage Evolution is one historical accident piled atop another. A mutation or recombination that happens to enhance survival or reproduction is preserved. Once it exists, other evolutionary accidents can build on it. In "Évolution et bricolage" Jacob (1977) described this phenomenon as follows (slightly edited). It is hard to realize that the living world as we know it is just one among many possibilities-that its actual structure results from the history of the earth. Yet living organisms are historical structures, literally creations of history. They represent, not a perfect product of engineering, but a patchwork of odd sets pieced together when and where opportunities arose. The opportunism of natural selection is not simply a matter of indifference to the structure and operation of its products. It reflects the very nature of a historical process, full of contingency. [Evolution] works like a tinkerer, a tinkerer who does not know exactly what he is going to produce but uses whatever odds and ends are at his disposal. What he ultimately produces is generally related to no special project. Each product can be used in a number of different ways. What they have in common is "it might be of some use." For what? That depends on future opportunities. Yet each evolutionary product embodies a constructed causal relationship. The environment on which the causal mechanism depends is almost always the product of a history of historical accidents. Evolution thus reflects both causality in the sense of constructed causal relationships and randomness in the form of the accidental environments on which the causal relationships depend Conclusion Causality, which can be immensely confusing when one attempts to see it as a relationship between events makes much more sense when understood in terms of manipulable causal relationships. From that perspective causality can be seen as a foundation for both computing and complexity. References Aaronson, Scott (2014) This review of Max Tegmark's book also occurs infinitely often in the decimal expansion of π. Shetl-Optimized. Dowe, Phil (2000) Physical Causation, Cambridge University Press. Hiddleston, Eric (2005) Review of Woodward, Making things happen. The Philosophical Review, Vol. 114, No. 4 (Oct., 2005), pp. 545-547 Hoefer, Carl (2015, forthcoming) Causal Determinism. Zalta, Edward N. (ed), The Stanford Encyclopedia of Philosophy. Imai, Kosuke, Dustin Tingley, and Teppei Yamamoto (2013) Experimental Designs for Identifying Causal Mechanisms. Journal of the Royal Statistical Society: Series A (Statistics in Society) 176, no. 1 (January 2013): 5-51. Jacob, Francois (1977) Evolution and Tinkering. Science. Vol. 196, No. 4295. (Jun. 10, 1977), pp. 1161-1166. Jacob, Francois and Jacques Monod (1961) Genetic regulatory mechanisms in the synthesis of proteins. Journal of Molecular Biology 3: 318-56. Little, Daniel (2004) Causal mechanism. Michael Lewis-Beck, Alan Bryman, and Tim Futing Liao (eds) Encyclopedia of Social Science Research Methods, Sage Publications. Paul, Laurie and Ned Hall (2012) Causation: a user's guide. Oxford University Press. Pearl, Judea (2009) Causality (2e). Cambridge University Press. Randi, James (2006) James Randi exposes Uri Geller and Peter Popoff. YouTube. Savageau, Michael A. (2012) Phenotypes and Design Principles in System Design Space. In Walhout, Marian, Marc Vidal, Job Dekker (eds) Handbook of Systems Biology: Concepts and Insights. Academic Press. Schaeffer, Jonathan (2014) The Metaphysics of Causation. Zalta, Edward N. (ed.) The Stanford Encyclopedia of Philosophy (Summer 2014 Edition). 12 12 War, A. R., Paulraj, M. G., Ahmad, T., Buhroo, A. A., Hussain, B., Ignacimuthu, S., & Sharma, H. C. (2012). Mechanisms of plant defense against insect herbivores. Plant Signaling & Behavior, 7(10), 1306-1320.  Weinberg, Steven (1995). Reductionism redux. The New York Review of Books. Wikipedia (2015) Rube Goldberg machine. Wikipedia. Woodward, James (2003) Making thigs happen. Oxford University Press. Woodward, James (2013) Causation and Manipulability. Edward N. Zalta (ed.)The Stanford Encyclopedia of Philosophy (Winter 2013 Edition). Woodward, James (2012/forthcoming) A Functional Account of Causation, Or, A Defense of the Legitimacy of Causal Thinking by Reference to the Only Standard that Matters-Usefulness (as Opposed to Metaphysics or Agreement with Intuitive Judgment). (2012 Philosophy of Science Association Presidential Address). Forthcoming in Philosophy of Science.


With a diverse sample (N = 231 paired responses) of employees from various organizations in Pakistan, the authors tested for the main effects of perceived organizational politics and psychological
          capital on turnover intentions, job satisfaction, and supervisor-rated job performance. They also examined the moderating influence of psychological capital in the politics–outcomes relationships. Results provided good support for the proposed hypotheses. While perceived organizational politics was associated with all outcomes, psychological capital had a significant relationship with job satisfaction and supervisor-rated performance only. As hypothesized, the negative relationship of perceived organizational politics with job satisfaction and supervisor-rated performance was weaker when psychological capital was high. However, the result for turnover intentions was counter to expectations where the politics–turnover intention relationship
          was stronger when psychological capital was high.

Philosophy

PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 1 Combined Effects of Perceived Politics and Psychological Capital on Job Satisfaction, Turnover Intentions, and Performance Muhammad Abbas Faculty of Management Sciences Riphah International University, Sector I-14, Hajj Complex, Islamabad PAKISTAN Email:  Usman Raja* Faculty of Business Brock University 500 Glenridge Ave. St. Catharines, ON L2S 3A1, CANADA Email: ;  Wendy A. Darr Defense Scientist Directorate of Military Personnel Research and Analysis National Defense Headquarters Ottawa, ON, Canada K1A 0K2 Email:  Dave Bouckenooghe Faculty of Business Brock University, 500 Glenridge Ave. St. Catharines, ON L2S 3A1 CANADA Email:  * Corresponding author Acknowledgements: This research was partially supported by Brock University research grant 112-348066. The authors would like to thank Gary Johns, Gary Greguras (Action Editor), and two anonymous reviewers for their valuable suggestions that helped us in improving this paper. We also thank Aliya Moeen Zafar for her help in proofreading and editing this paper. Citation: Abbas, M. Raja, U., Darr, W., & Bouckenooghe, D. (August 2012). Combined Effects of Perceived Politics and Psychological Capital on Job Satisfaction, Turnover Intentions, and Performance. Journal of Management DOI: 10.1177/0149206312455243. This is final accepted version of the article (without proofread). The final publication is available at  PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 2 Abstract With a diverse sample (n = 231 paired responses) of employees from various organizations in Pakistan, we tested for the main effects of perceived organizational politics and psychological capital on turnover intentions, job satisfaction, and supervisor rated job performance. We also examined the moderating influence of psychological capital in the politics - outcomes relationships. Results provided good support for the proposed hypotheses. While perceived organizational politics was associated with all outcomes, psychological capital had a significant relationship with job satisfaction and supervisor rated performance only. As hypothesized, the negative relationship of perceived organizational politics with job satisfaction and supervisor rated performance was weaker when psychological capital was high. However, the result for turnover intentions was counter to expectations where politics - turnover intention relationship was stronger when psychological capital was high. Keywords: Perceived Politics; Psychological Capital; Job Performance; Job Satisfaction; Turnover Intentions PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 3 COMBINED EFFECTS OF PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL ON JOB SATISFACTION, TURNOVER INTENTIONS, AND PERFORMANCE Over the past couple of decades, perceived organizational politics (POP) has remained an important subject of inquiry in the field of organizational behavior and is commonly viewed as a source of detrimental consequences for organizational members (e.g., Chang, Rosen, & Levy, 2009; Ferris, Russ, & Fandt, 1989). However, despite two recent meta-analytic studies, the effects of POP on outcomes are still inconclusive. For example, Miller, Rutherford, and Kolodinsky's (2008) meta-analysis examining perceived politics and various employee outcomes such as job stress, job satisfaction, turnover, and organizational commitment suggests that POP is generally detrimental to personal and organizational effectiveness; yet their findings also reveal variation in effects across outcomes and certain settings. Specifically, the effects for job performance were much smaller than for other outcomes, and public sector employees were more likely to leave the organization in the face of organizational politics compared to private sector employees. In addition, the effects for organizational commitment were much lower in international samples than in domestic samples, suggesting the need for further exploration of POP theory in different cultures to determine its boundary conditions. Pointing to the lack of a theoretical understanding of how perceptions of politics influence employee outcomes, Chang et al. (2009) called for future researchers to examine the contextual and individual difference factors as moderators in such relationships. Although few studies have attempted to explore the moderating role of individual difference variables in the relationship between perceived politics and various outcomes, there remains a lack of understanding of the influence of an individual's composite psychological resources, particularly PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 4 hope and self-efficacy, on the relationship between perceived politics and outcomes such as turnover intentions, job satisfaction, and job performance. For example, Kacmar, Collins, Harris, and Judge (2009) found that Core Self Evaluations (which includes generalized self-efficacy) exacerbated the relationship between POP and job performance. Bozeman, Perrewe, Hochwarter, and Brymer (2001) found some mixed evidence whereby self-efficacy intensified the negative effects of perceived politics on job satisfaction; however, it did not moderate between POP-turnover intentions and POP-job stress relationships. On the contrary, we draw upon Conservation of Resource Theory (Hobfoll, 2011) to argue that psychological capital (PsyCap) comprising hope and self-efficacy will act as 'a solid resource reservoir' (Hobfoll, 2002: 318) and reduce the negative effects of politics on work outcomes. Thus, the study of psychological capital as a holistic core construct would better explain the moderating role of such constructs in the POP - outcomes relationships and would advance further knowledge in this domain. In addition, it is important to note that the majority of studies in this domain of research have been conducted in developed countries of North America and Europe. Tsui, Nifadkar, and Ou (2007) suggested that unless we test the theories largely developed in the US in non-Western settings, researchers and practitioners would have little confidence about their generalizability in other regions. We believe that our study will address this gap as it provides a rare opportunity to examine the applicability and validity of concepts largely developed in Western cultures. THEORY AND HYPOTHESES POP, PsyCap, and Workplace Outcomes Politics is an inevitable component of an organization's social fabric, which different people may perceive differently. Despite some discussion that some individuals thrive on PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 5 politics, using it to their advantage through the development of political skill (Ferris, Perrewe, Anthony, & Gilmore, 2000), this treatment of POP has typically been made in reference to the upper organizational echelon of executives (see Perrewe, Ferris, Frink, & Anthony, 2000). In the current study, we define perceived organizational politics as an individual's perceptions of others' self-interested acts or behaviors, frequently associated with manipulation of organizational policies, often using coercive tactics even at the expense of others for short-term gains (Kacmar & Ferris, 1991). These behaviors are perceived as subversive and contradict with the interests of other individuals and the organization (Vigoda, 2000). As an antecedent to workplace outcomes, POP has generally been regarded as a stressor. For example, while examining stressors, Cavanaugh, Boswell, Roehling, and Boudreau (2000) found that POP loaded on a factor called hindrance stressors. The 'organizational development literature' also conceives perceived politics as a stressor that has detrimental impact on a person's resources. More specifically, Crawford, Lepine, and Rich (2010) suggest that POP activates an energy depletion process whereby an employee's sustained increases in effort to meet the perceived demands is met with an increase in compensatory actions and psychological processes that drain a person's individual resources. In addition, Chang et al. (2009) metaanalytically examined perceptions of politics as a hindrance stressor to find a stress-related connection to performance. In the light of these findings, POP is regarded as a hindrance stressor in the present examination. Despite recent meta-analytic evidence for variation in the effects of POP on outcomes (e.g., Miller et al., 2008), perceived politics can be summarized as having a generally positive relationship with turnover intentions (Chang et al., 2009), and a negative relationship with job satisfaction (Chang et al., 2009; Ferris & Kacmar, 1992) and job performance (Vigoda, 2000). PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 6 There is also some evidence available for the harmful effects of perceived organizational politics across cultures. For example, Vigoda (2001) found that British and Israeli employees reported similar levels of organizational politics at the workplace, however British employees responded to perceived politics with higher turnover intentions than Israeli employees. Vigoda (2001) attributed these findings to the difference in power distance (PD) between both cultures. Britain ranks higher on the national cultural dimension of power distance as compared to Israel (Hofstede, 1983). In high power distance cultures, individuals usually accept a hierarchical order in which everybody has a place. In these cultures, interpersonal conflict is considered a disruption of ordinary life (Hofstede, 1991). Similar to Britain, Pakistan also ranks high on power distance (Hofstede, 1983). In addition, Pakistan scores high uncertainty avoidance (UA), reacting adversely to uncertainty or a lack of control. Hofstede (2001) suggests that the combination of these two dimensions results in situations where leaders have ultimate power and authority, and that rules, laws, and regulations are developed to reinforce such leadership. In such a context, formal rules and regulations exist to further managerial interests at the expense of subordinates (Kacmar & Ferris, 1991), prompting turnover and lowered job satisfaction as employees' reactions to perceived politics in the workplace. Hence, we expect to replicate the findings that perceived politics would have harmful effects on outcomes in Pakistan. Hypothesis 1: Perceived organizational politics will be positively related to turnover intentions and negatively related to job satisfaction and job performance. Lately, researchers in domains of positive organizational behavior have stressed the need to focus on positive strengths and well-being of individuals in the workplace (Luthans & Youssef, 2007). The positive psychological approaches have emerged with a focus on what is right with people, rather than the traditional approaches of what is wrong with people (Luthans, PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 7 2002). This line of thinking has resulted in the coining of a term known as psychological capital (Avey, Luthans, & Youssef, 2010). Although psychological capital (PsyCap) comprises of four components named hope, optimism, self-efficacy, and resilience (Luthans, Youssef, & Avolio, 2007), research considers hope and efficacy to be the most significant in predicting various work-related outcomes (e.g., Luthans, Avolio, Avey, & Norman, 2007; Stajkovic & Luthans, 1998a; Youssef & Luthans, 2007). Efficacy is "the employee's conviction or confidence about his or her abilities to mobilize the motivation, cognitive resources, or courses of action needed to successfully execute a specific task within a given context" (Stajkovic & Luthans, 1998b: 66). Similarly, hope is "a positive motivational state that is based on an interactively derived sense of successful (a) agency (goal-directed energy) and (b) pathways (planning to meet goals)" (Snyder, Irving, & Anderson, 1991: 287). Conceptually, self-efficacy and hope are assumed to be more significant factors than optimism and resiliency in predicting attitudes and organizational behavior (Bandura, 2012). Self-efficacy is considered to best meet the inclusion criteria for PsyCap in positive organizational behavior (Luthans, 2002). Similarly, of the three remaining facets of PsyCap 'hope' is the strongest predictor of work related outcomes and shares the strongest underlying common denominator with self-efficacy and (Luthans, 2002; Magaletta & Oliver, 1999; Youssef & Luthans, 2007). Efficacy and hope share the components of internalized motivation and energy, or the positive expectation of success for the reason of belief in one's individual abilities. Highly efficacious and hopeful employees would set challenging goals for themselves and selfselect into challenging assignments with motivation and tenacious effort toward success. Therefore, we focus on the efficacy and hope dimensions of psychological capital in this study. PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 8 Previous research has found PsyCap to be positively associated to job performance and satisfaction (Luthans, Avolio, et al., 2007), and negatively associated to organizational cynicism and turnover intentions (Avey et al., 2010). Based on its definition, individuals with high PsyCap are believed to possess the cognitive capacity of self-regulation (Bandura, 1997) that offers initiative, energy, and self-discipline necessary to reach one's goals (Luthans & Youssef, 2007). Thus we believe that being personal and psychological in nature, psychological capital will have similar effects on outcomes as those observed in US settings. Psychological capital, especially hope and self-efficacy, will give individuals more confidence and stimulate positive thinking, which would result in better performance, higher satisfaction, and lower possibility of leaving the job. Therefore, we suggest that: Hypothesis 2: PsyCap will be negatively related to turnover intentions and positively related to job satisfaction and job performance. The Moderating Role of Psychological Capital Recent studies have shown the relevance of COR theory to serve as a conceptual foundation for the role of individuals' psychological resources to cope with harmful effects of organizational politics (Kapoutsis, Papalexandris, Nikolopoulos, Hochwarter, & Ferris, 2011). Hindrance stressors tend to dampen motivation, which thwarts performance and personal goal attainment and growth (LePine, Podsakoff, & LePine, 2005). This theory helps in delineating the processes by which resources such as psychological capital assist individuals to cope with stressors. Individuals who possess key resources such as hope and self-efficacy 'might be more capable of selecting, altering, and implementing their other resources to meet stressful demands' (Hobfoll, 2002: 308). When faced with an environmental stressor (e.g., organizational politics), individuals PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 9 exert efforts to successfully cope with it in order to maintain a balance (Hobfoll, 2011). The success of these efforts depends on the psychological resources these individuals possess (Treadway et al., 2005).Therefore, individual differences in internal psychological resources are likely to play an influential role in the attribution of resource loss as salient. Here, resource loss could refer to perceived loss of tangible goals due to politics in the workplace or to a perceived loss of cognitive or emotional coping resources dedicated to addressing politics as a stressor. We argue that high PsyCap individuals, because of their level of confidence in pursuing challenging tasks (Bandura, 1997), their capacity to derive multiple pathways to be successful (Snyder, 1994), and their ability to persevere in the face of obstacles (Stajkovic & Luthans, 1998a), are less likely to perceive organizational politics as threatening or harmful. These individuals possess the cognitive capacity of self-regulation (Bandura, 1997) that offers initiative, pro-activeness, and self-discipline necessary to reach the desired goals, even when there is a lack of extrinsic motivators (Luthans & Youssef, 2007) and absence of feedback (Judge, Jackson, Shaw, Scott, & Rich, 2007). Therefore, they are less likely to experience the typical negative outcomes (e.g., lowered job satisfaction and performance) associated with organizational politics. Seligman and Csikszentmihalyi (2000) posit that hope plays the role of a buffering agent against psychological distress, addiction, and dysfunctional behavior. Studies have demonstrated a strong relationship between hope and academic and athletic performance, mental and physical health, and the ability to cope with adversity (Snyder, 1994; Snyder et al., 1991). Similarly, Caprara, Barbaranelli, Pastorelli, and Cervone (2004) investigated the ability of efficacy beliefs to predict psychosocial outcomes among high school students. These authors found that selfefficacy beliefs predicted lower problem-behaviors (depression and aggression) and attainment PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 10 of greater grades. Moreover, high efficacious individuals are less likely to expect failures or loss of confidence when faced with negative feedback, setbacks, uncertainties, and difficulties (Bandura & Locke, 2003). When combined, these psychological resource capacities form the cognitive, emotional, and motivational bases (Bandura & Locke, 2003; Seligman & Csikszentmihalyi, 2000) through which individuals mitigate the detrimental effects of negativity (Youssef & Luthans, 2007). Based on these arguments, we believe that when individuals perceive the organizational activities and procedures to be politically driven, their psychological capital may help them to minimize the salience of resource loss associated with these activities, allowing them to cope better with these stressors, thereby reducing the influence of POP on outcomes. Consequently, we suggest: Hypothesis 3: PsyCap will moderate the relationship between POP and outcomes (turnover intentions, job satisfaction, and job performance) such that the relationship will be weaker when PsyCap is high. METHODS Sample and Data Collection Procedures Perceptions of politics can vary considerably across organizations. In order to capture maximum variance in politics, we decided to collect data from a variety of organizations. Through personal and professional contacts of the first author, we were able to gain access to employees in six branches of private banks, local offices of two textile-manufacturing firms, three offices of a government ministry, and customer service offices of a telecommunication company in Faisalabad, which is the third largest city of Pakistan. We decided to target all whitecollar employees in each location for two reasons. First, we believe that organizational politics is PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 11 more likely to play a role among managers and professional workers because they have to manage people and resources. Second, due to low education levels, we believed that lower level blue collar workers would not be able to respond to a questionnaire in English effectively. We collected data through onsite administration of a questionnaire with self and supervisory-report versions. A cover letter explained the purpose of the study to the respondents, assured them of strictest confidentiality of responses, and mentioned that participation was voluntary. Respondents completed the self-report version that contained items related to POP, PsyCap, turnover intentions, and job satisfaction. In addition, they reported their name, age, gender, occupational level, education, and work experience in the demographics part of the survey. The supervisor of each respondent completed the supervisor-report version that contained questions on job performance. Both the respondents and their supervisors returned the completed questionnaires to one of the authors without having access to each other's responses. Each supervisor knew his / her subordinates for more than six months and had done at least one performance appraisal for him / her. Of the 300 distributed questionnaires, we received 237 completed self-report responses. We were able to get supervisor reports from 79 supervisors for 231 of the respondents. Therefore, our final response rate for the 231 usable paired (231 employee and 231 supervisor responses) responses was 77%. We distributed 48 surveys among the government workers, 154 in bank branches, 33 in the telecom company, and 65 in the textile firms. The response rates for government offices, banks, telecom, and textile firms were 75%, 78%, 76%, and 75% respectively. The majority of respondents (80.1%) were male with an average age of 31 years (SD = 8.1). The sample included several occupational levels comprising 16% entry level (clerical and IT staff) workers, 80% supervisory and middle managers, and 4% upper middle and topPERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 12 level managers. The average tenure was 4.80 (SD = 6.48) years. About 31% of the respondents had an undergraduate university degree while 69% held graduate degrees. A total of 79 supervisors reported for the 231 respondents, which could result in nesting of data. With supervisor as a grouping variable, we ran the null model in HLM to calculate between and within group variance for job performance in our dataset. This procedure estimated whether it was feasible to run a more complex model controlling for nesting of data based on supervisor as the higher-order level in our dataset. The results revealed that within group variance (R2 = .27) was substantially higher than between group variance (R2 = .08) and the F statistic for the ratio of the two variances was not significant (F (78, 152) = .22, n.s). Put differently, the data suggest that supervisors as a grouping variable do not explain sufficient variance to justify the use of HLM analysis controlling for nesting of data (Bryk & Raudenbush, 1992). Measures All constructs were measured using self-reported instruments except for job performance, which was measured using supervisory ratings to avoid method bias issues. Responses for all variables, with exception of PsyCap, were assessed using a 5-point Likert type scale with anchors of 1 = 'strongly disagree', 2 = 'disagree', 3 = 'neither disagree/nor agree', 4 = 'agree', and 5 = 'strongly agree'. The responses for psychological capital were measured using a 6-point Likert-scale with anchors ranging from 1 = 'strongly disagree', 2 = 'disagree', 3 = 'somewhat disagree' 4 = 'somewhat agree', 5 = 'agree', to 6 = 'strongly agree'. For all measures, higher score corresponded to higher levels of the construct. Perceptions of Organizational Politics (POP). We used the 12-item Perceptions of Organizational Politics Scale (POPS) by Kacmar and Ferris (1991) to assess this construct. This PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 13 scale contains three sub-dimensions of perceived politics: general political behavior (six items), go along to get ahead (four items), and pay and promotion policies (two items). Examples of items include "people build themselves up by tearing others down", for the first dimension, "employees are encouraged to speak out (reverse-coded)" for the second, and "Pay and promotion policies are not politically applied (reverse-coded)" for the third dimension. As we were interested in examining the effects of overall perceived politics on outcomes, we conducted a second order confirmatory factor analysis to see if the three-dimensional construct did load on to a single latent factor. The results of CFA revealed a good fit for a latent single factor model (2 = 84.76, df = 53, CFI = .94, GFI = .94, IFI = .95, RMSEA = .05). Therefore, we used an additive measure by taking average of all items to create overall POP such that high scores reflected high perceived politics1. This treatment of POP measure has been used in past research (e.g., Randall, Cropanzano, Bormann, & Birjulin, 1999; Rosen, Levy, & Hall, 2006). Cronbach's alpha reliability of the POP measure was .73. Psychological Capital (PsyCap). We measured efficacy and hope using 12-items (six items for each measure) from Psychological Capital Questionnaire (Luthans, Youssef, et al., 2007). Examples of items include "if I should find myself in a jam at work, I could think of many ways to get out of it" for hope; "I feel confident analyzing a long-term problem to find its solution" for efficacy. We conducted a second order CFA to see if both hope and efficacy loaded on to a single latent factor. Results yielded a good fit for a latent single factor model (2 = 102.91, df = 52, CFI = .95, GFI =.94, IFI = .95, RMSEA = .06). Therefore, to create overall psychological capital, we averaged scores on all 12 items such that a high score reflected high psychological capital. The internal consistency reliability of PsyCap was .89. 1 We ran our analyses using a measure based on mean of the means of dimensions. The results did not differ compared to the additive measure. PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 14 Outcomes. A 3-item scale by Vigoda (2000) was used to measure turnover intentions. This measure included items such as "I often think about quitting this job". The reliability of this measure was .76. We measured overall job satisfaction using a 6-item scale developed by Agho, Price, and Mueller (1992), which contained questions such as "I feel fairly well satisfied with my present job" and "I find real enjoyment in my work." The reliability of this measure was .67. Supervisor responses to a 7-item scale developed by Williams and Anderson (1991) were used to measure job performance. Sample items include, "This person adequately completes assigned duties" and "This person performs tasks that are expected of him/her." The alpha reliability was .77. Control Variables. We used age and tenure as control variables because of their possible effects on job outcomes. A one-way ANOVA comparing job satisfaction, job performance, and turnover intentions across gender, education, and organizations revealed that there were significant differences in turnover intentions (F = 34.02, p < .000) and job satisfaction (F = 14.60, p < .000) across organizations. Post-hoc analyses showed that the differences were only between the two groups of organizations in the public and private sectors. Hence, we used a dummy variable (0 = "Private," 1 = "Public") to control for the effects of organization type. RESULTS POP, PsyCap, and Outcomes Table 1 shows the descriptive statistics, bivariate correlations, and estimates of reliability (coefficient alpha) for all measures. All the zero-order bivariate correlations were in the expected direction. -----------------------------Insert Table 1 about here PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 15 ------------------------------ We used multiple linear regression analyses to test all main effect hypotheses (H1 and H2). We entered age, tenure, and organizational type in the first step followed by the independent variables. Table 2 (step 3) presents the results for the main effects of POP and PsyCap on the outcomes. POP was positively related to turnover intention (β = .26, p < .001) and negatively to job satisfaction (β = -.29, p < .001) and job performance (β = -.21, p < .05). These results support hypothesis 1. Similarly, Table 2 shows that psychological capital was positively related to job satisfaction (β = .56, p < .001) and job performance (β = .54, p < .001), but its relationship with turnover intentions (β = -.01, n.s) was not significant. These results render support to hypothesis 2 for satisfaction and performance only. -----------------------------Insert Table 2 about here ------------------------------ Moderating Influence of PsyCap We used moderated multiple regression (MMR) analyses (Cohen, Cohen, West, & Aiken, 2003) to test hypotheses 3. We entered the control variables in the first step followed by independent and the moderator variables in the next step. In the third step, we entered a product term of independent and moderator variable, which if significant, confirmed moderation. We centered the variables by subtracting the overall mean from the individual values for the moderated regression analyses. In addition, we also obtained the variance inflation factor (VIF) scores (Hair, Anderson, Tatham, & Black, 1998) and the tolerance statistics (Tabachnick & PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 16 Fidell, 2001), which measure the extent to which collinearity among predictors affects the precision of a regression model. VIF scores of less than 5 (Chatterjee & Price, 1991) and tolerance scores above .10 (Hair et al., 1998) are typically considered acceptable. The VIF scores were below 3 (Tolerance > .3) in all analyses indicating that multicollinearity was not a problem. Results presented in Table 2 (step 3) show that controlling for the effects of POP and PsyCap, the interaction term of POP x PsyCap was significant for turnover intentions (β = .14, p < .05; ΔR2 = .02, p < .05), job performance (β = .33, p < .001; ΔR2 = .09, p < .001), and job satisfaction (β = .17, p < .01; ΔR2 = .02, p < .01). The additional variance explained by the interaction term falls within or exceeds the typical range for moderator effects in nonexperimental field studies (e.g., Chaplin, 1991). We plotted the significant interactions for high and low (Mean ± SD) values of the moderator. The plots of the significant interactions are displayed in figures 1 through 3. Figure 1 shows that, contrary to our hypothesis, the positive POP-turnover intentions relationship was stronger when PsyCap was high. Simple slope tests using the procedure recommended by Aiken and West (1991) revealed that the slope for high levels of PsyCap was significant (β = 0.79, p < .001), however the slope for low levels of PsyCap was not significant (β = -.23, ns). Figure 2 shows the plot of significant interaction for job satisfaction. The slope for high psychological capital was not significant (β = -.04, ns), but the slope line for low psychological capital was significant (β = -.74, p < .01). Figure 3 shows the plot of simple slopes for job performance. The relationship between perceived politics and job performance was significantly negative for low levels of PsyCap (β = -1.26, p < .001) and significantly positive for high levels of PsyCap (β = .32, p < .01). Hence, the results supported hypothesis 3 for job performance and job satisfaction only. PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 17 ----------------------------------------------Insert Figures 1 through 3 about here ------------------------------------------------ Figures 2 and 3 indicate that there was one outlier cell, where psychological capital was low and perceived organizational politics was high, tended to have greater effects. Therefore, we conducted the Bobko procedure (Bobko, 1986) as a robustness check for ordinal interaction effects. The results for the first contrast (comparing means for low politics and high PsyCap; low politics and low PsyCap; high politics and high PsyCap) using a one-way analysis of variance showed that there were no significant differences between the three means (Fperformance = 1.59, n.s.; F satisfaction = 1.64, n.s.). The second contrast revealed that these three conditions were significantly different from the condition in which respondents were scoring high on politics and low on PsyCap (t performance = 5.19, p < 0.001; t satisfaction = 4.49, p < 0.001). DISCUSSION Despite general agreement amongst researchers, empirical evidence has revealed variations in the influence of POP on outcomes. In this research, we not only tested for the moderating role of psychological capital in accounting for some of the observed variation in effects, but also incorporated the COR theoretical framework to better understand how psychological capital of hope and efficacy can play a role in employee efforts to address POP as a hindrance stressor. Our findings clearly support the assertion that when employees perceive politics in the workplace, it reduces their satisfaction and performance and increases the likelihood that they would leave the organization. These findings provide support for the idea of perceived politics PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 18 being detrimental to desired outcomes at workplace. The results of our study also support the idea that psychological capital has a positive effect on desired outcomes such as job satisfaction and job performance, but not intentions to quit. In addition, we found good support for the moderating influence of PsyCap in the POP-outcomes relationship. Interestingly, and contrary to our expectations, the negative relationship between perceived politics and intentions to quit was stronger when PsyCap was high. In retrospect, it is possible that individuals with high psychological capital, being more skillful and confident, think of leaving their jobs if they perceive high politics. They might want to seek better working environment and start looking for options in the wake of high-perceived politics. For example, it has been suggested that high performers would be more likely to quit when salaries and promotion policies are not aligned (Allen & Griffeth, 1999), as they have greater tangible resources such as a proven performance track record or other employment opportunities to draw upon (Jackofsky, 1984). Moreover, research on employability suggests that an organizational environment that does not foster its members' development and employability, increases employees' turnover intentions (Nauta, van Vianen, van der Heijden, van Dam, & Willemsen, 2009). Our findings suggest that psychological resources function the same way, equipping individuals with the cognitive and emotional resources necessary to push them away from a threatening political workplace. The results for moderating effects of PsyCap in the relationship between POP and job satisfaction and performance were in the expected direction. In both cases, the observed negative relationship was stronger when psychological capital was low. The results indicate that perceived organizational politics is going to be a bigger concern for those with low psychological capital. Perceived politics does not seem to have negative impact on the satisfaction and performance of PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 19 individuals with high psychological resources (i.e., hope and efficacy). Our finding that psychological capital comprising hope and efficacy acts as a threatneutralizer by reducing the negative effects of politics on performance deserves further attention as it apparently contradicts with the findings of Kacmar et al. (2009). Drawing upon trait activation theory, Kacmar et al. (2009) found that core self-evaluations (which include generalized self-efficacy) intensified the deleterious effects of perceived politics on job performance. We believe that efficacy in conjunction with hope creates a positive resource for individuals that help them to take up the challenge of perceived politics instead of reacting negatively to it. Social psychologists argue that these psychological resources should be studied collectively, as they do not act in isolation (Fredrickson, 2001; Youssef & Luthans, 2007). Instead, such resources together provide support to each other through a shared underlying mechanism (Luthans, Avolio et al., 2007) that binds them and helps individuals to use them effectively when faced with stressful situations (Hobfoll, 2002). More specifically, a person with no hope and high efficacy is less likely to effectively deal with hurdles as compared to an individual who not only has the required confidence but also has hope that his / her efforts would lead to positive outcomes. We believe that our findings support this line of thought and confirm the idea that efficacy and hope together act to minimize the harmful effects of POP on job outcomes. A comparison of the zero-order correlations reported in Table 1 against the meta-analytic uncorrected associations reported in Miller et al. (2008) provides an opportunity to compare results for main effects in Western cultures to those examined in this study. With respect to turnover intentions and job performance, it appears that our obtained associations (r =.30 for turnover intentions and r = -.08 for job performance) are almost identical to those found for PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 20 Miller et al's (r =.33 for turnover intentions and r = -.09 for job performance) domestic samples (i.e., North American, generally thought to be low on the cultural values of power distance and uncertainty). Although the perceived politics - satisfaction association was almost half the size (r = -.21) compared to that observed in Miller et al's meta-analysis for domestic samples (r = -.40), the confidence interval (-.73 to -.17) included the correlation observed in our study. Taken together, these findings suggest that results from the past research in Western context generalize well to Pakistani context. Perceived organizational politics, perhaps, is much more personal in nature and less susceptible to contextual influences. This examination is consistent with the call to examine theories, mostly developed and tested in Western settings, in a non-Western context. Our deliberate exploratory examination of cultural context is consistent with Johns' (2006) directions for future researchers in the field of organizational behavior. While this study provides some evidence for external validity or generalizability of the examined relationships, it also points to the need for more direct examinations of context by incorporating discrete contextual features (e.g., cultural values) in future examinations of POP. Implications for Practice Our study provides some valuable managerial implications. For example, managers should be wary of the harmful implications of workplace politics. They should address potential contributors to perceived organizational politics, such as ambiguous policies and procedures, poor communication, and lack of proper feedback and guidance to minimize the adverse effects on employees. Managers of organizations that are going through mergers, downsizing, or restructuring should be even more vigilant, as these processes also tend to increase uncertainty and politics in the work environment. It would be prudent for organizations to re-examine their selection criteria in hiring individuals, to include characteristics such as hope and efficacy, as PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 21 these can buffer new hires from the influence of politics. The design and implementation of training interventions can benefit by incorporating methods that help in enhancing the psychological resources, especially hope and efficacy of employees so that they are better equipped to cope with demanding and stressful work environment. Strengths and Limitations The current study has several strengths. First, responding to the call of Fineman (2006), this study integrates the positivityand negativity-oriented research. In particular, we enhance our understanding of the organizational politics and psychological capital theories in a new cultural setting significantly different from North America and Europe. Exploring the main and moderating effects in such setting extends our understanding and provides evidence for external validity of research domains dominated by Western samples. Second, we collected our filed data from multiple sources, which reduced the possibility of method bias. Detection of significant interactions for self-reported perceived politics and supervisory-reported performance, where the interaction accounted for 9% additional variance, is rare. Third, this study provides strong evidence for main effects of overall psychological capital on job satisfaction, and supervisorrated job performance. Finally, our findings provide support for the role of psychological capital (i.e., hope and self-efficacy combined) as a threat-neutralizer as compared to previous findings of efficacy as a threat-amplifier. This study has several limitations that need to be noted. One of the limitations has to do with common method bias. Although we attempted to circumvent this possibility by assessing job performance using supervisory ratings, this was not the case with the other examined variables. However, the obtained results for the main effects of POP are generally consistent when compared to those reported in past research. Moreover, significant interactions suggest that PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 22 method variance was not an issue as it works against detection of such interaction effects. A second limitation is the slightly lower reliability of job satisfaction (α = .67). Nevertheless, the obtained associations between POP and outcomes are consistent with the meta analytic findings of Miller and colleagues (2008). A third limitation is that we included only two of the four dimensions of psychological capital. Although we do not expect our findings to change if the remaining two dimensions are included because efficacy and hope are the dominant dimensions and have stronger effects, some differences in effect size cannot be ruled out. Future Research Directions Future research in this area should examine the role of other plausible individual and contextual moderators in the relationship between perceived politics and outcomes. For example, exploring the effects of the Big Five traits on the POP-outcomes relationship might provide insight into our understanding of the interplay of person and situation factors in determining various attitudinal and behavioral outcomes. Acknowledging possible differences in the domain of POP across nations, future research needs a direct comparison of non-Western and Western samples to explore the moderating influence of discrete cultural contextual factors (e.g., cultural values). Future studies should also focus on providing a more detailed analysis of the dimensionality of POP and their relative influence on job outcomes. Similarly, research may continue to explore the viability and vitality of PsyCap as a construct that can help improve our understanding of organizational behavior. Being a state-like characteristic that is amenable to development, psychological capital may hold better promise for organizational effectiveness against the dominant trait theories. PsyCap, being a composite of positive psychological resources, has inherent proactive coping mechanism and goal-orientation that may buffer against challenge and hindrance related stressors such as role stressors, heavy PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 23 workload, time pressure, and job scope. Testing models that directly examine such role of PsyCap would provide more insight into the buffering capacities of these resources. Conclusion Asia has an important role in the global economy as multinationals are increasingly moving to Asian regions. Unless we test the theories largely developed in the US in non-Western settings, researchers and practitioners would have little confidence about their generalizability in those regions (Tsui et al., 2007). Our study provides some insights into the generalizability of concepts such as perceived organizational politics and psychological capital in Pakistan. 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Journal of Management, 33, 774-800. PERCEIVED POLITICS AND PSYCHOLOGICAL CAPITAL 30 Table 1 Means, Standard Deviations, Correlations, and Reliabilities Note. N = 231; Alpha reliabilities presented in parenthesis. POP = Perceived Organizational Politics; PsyCap = Psychological Capital. a. Organizational type: 0 = Private; 1 = Public. * p < .05 ** p < .01 Mean S.D 1 2 3 4 5 6 7 8 1. Age 30.82 8.10 -- 2. Tenure 4.89 6.49 .76** -- 3. Organization a 0.17 0.37 .36** .43** -- 4. PsyCap 4.52 0.82 .01 .08 .12 (.89) 5. POP 3.06 0.54 -.03 -.01 -.05 .11 (.73) 6. Turnover Intentions 2.92 0.93 -.30** -.29** -.35** -.05 .30** (.76) 7. Job Satisfaction 3.62 0.52 .14* .15* .24** .49** -.21** -.29** (.67) 8. Job Performance 3.80 0.59 -.01 .03 .05 .43** -.08 -.09 .53** (.77) 31 Table 2 Results for Main Effects and Moderated Regression Analyses Note. N = 231; POP = Perceived Organizational Politics; PsyCap = Psychological Capital. a. Organizational type: 0 = Private; 1 = Public. * p < .05 ** p < .01 *** p < .001 Turnover Intentions Job Satisfaction Job Performance β ∆R2 β ∆R2 β ∆R2 Step 1 Age -.16* .04 -.07 Tenure -.06 .03 .06 Organization a -.27*** .16*** .21** .06** .06 .00 Step2 Age -.16* .09 -.03 Tenure -.06 .01 .01 Organization a -.25*** .14** .00 POP .29*** -.24*** -.11* PsyCap -.05 .08*** .51*** .28*** .44*** .19*** Step 3 Age -.15* .09 -.01 Tenure -.06 .01 .00 Organization a -.26*** .14** .00 POP .26*** -.29*** -.21* PsyCap -.01 .56*** .54*** POP x PsyCap .14* .02* .17** .02** .33*** .09*** 32 Figure 1 Interactive Effects of PsyCap and POP on Turnover Intentions 33 Figure 2 Interactive Effects of PsyCap and POP on Job Satisfaction 34 Figure 3 Interactive Effects of PsyCap and POP on Supervisory-Rated Job Performance