Can a Theory-Laden Observation Test the Theory?

Franklin, Allan; Anderson, Melinda C.; Brock, Donna-Jean P.; Coleman, Susanne; Downing, John; Gruvander, A.; Lilly, J. Robert; Neal, Joseph M.; Peterson, David D.; Price, Mary F.; Rice, Rebecca M.; Smith, Larry; Speirer, S.; Toering, D.

doi:10.1093/bjps/40.2.229

Cited by 49 publications

(16 citation statements)

References 4 publications

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“…Models are better than previous ones if they will make more accurate, reliable predictions (Franklin et al, 1989) for a wide variety of experiments. Theories are better than established ones if they will subsume or explain more models or observations.…”

Section: Scientific Progressmentioning

confidence: 99%

Understanding Scientific Study via Process Modeling

Luk

2010

Found Sci

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This paper argues that scientific studies distinguish themselves from other studies by a combination of their processes, their (knowledge) elements and the roles of these elements. This is supported by constructing a process model. An illustrative example based on Newtonian mechanics shows how scientific knowledge is structured according to the process model. To distinguish scientific studies from research and scientific research, two additional process models are built for such processes. We apply these process models: (1) to argue that scientific progress should emphasize both the process of change and the content of change; (2) to chart the major stages of scientific study development; and (3) to define "science".

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Section: Scientific Progressmentioning

confidence: 99%

Understanding Scientific Study via Process Modeling

Luk

2010

Found Sci

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“…As noted at the outset, academics (Franklin et al, 1989;Guba and Lincoln, 1994) and philosophers of science (Kuhn, 1962), mostly worry about researchers so blinded by their theories/beliefs that they often see and report what is not really there -classic cases being the French discovery of ‗N waves' (Klotz, 1980;Nye, 1980), ‗water memory' (Maddox et al, 1988), and Fleischmann and Pons's (1989) reporting of their cold-fusion results. To help managers better see what they really aren't wanting to pay attention to -i.e., TIEs -we begin our analysis by defining ‗scale-free theories' that serve as ways of sharpening managers' abilities to see TIES early on.…”

Section: Causes Of Scalability: a Complexity Science Viewmentioning

confidence: 99%

“…The distinction between inconsequential stimuli (that can be ignored) and TIEs (that have the potential of spiralling up) should be attended to on the basis of evident scale-free theories, as we argue in this paper. Management scholars always worry about case writers who are ‗theory laden' -they see what their theories tell them to look for (Kuhn, 1962;Franklin et al, 1989;Guba and Lincoln, 1994 we describe fifteen theories about why scalability dynamics occur. In Section V we describe five of the fifteen that most readily explain the various scaling dynamics that Weick and Sutcliffe (2001) describe.…”

Section: About Here<mentioning

confidence: 99%

“…Mostly they simply aren't seen, or if seen, aren't paid attention to. Opposite the dominant fear of bias from theory ladenness (Kuhn, 1962;Churchland, 1979;Franklin et al, 1989;Guba & Lincoln, 1994), we pick up on the idea that it is quite often the case that ‗you don't see what you aren't looking for', which stems from cognitive blindness (Simons & Chabris, 1999, Simons & Rensink, 2005. Holland (2002) refers to as tiny initiating events (TIEs).…”

Section: Introductionmentioning

confidence: 99%

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Avoiding extreme risk before it occurs: A complexity science approach to incubation

McKelvey

Andriani

2010

Risk Manag

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“…He must show that the given test does not involve justification circularity, usually by showing that independent evidence for the auxiliaries has been acquired. Franklin et al (1989) challenged those who think that if observations are laden with the theory under test, that prevents a test of the theory. Could they come up with a workable example from actual science?…”

Section: Conclusion: Background Independencementioning

confidence: 99%

Testability and Candor

Roush

2005

Synthese

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On analogy with testimony, I define a notion of a scientific theory's lacking or having candor, in a testing situation, according to whether the theory under test is probabilistically relevant to the processes in the test procedures, and thereby to the reliability of test outcomes. I argue that this property identifies what is distinctive about those theories that Karl Popper denounced as exhibiting "reinforced dogmatism" through their self-protective behavior (e.g., psychoanalysis, Hegelianism, Marxism). I explore whether lack of candor interferes with the testing of theories, and conclude that (1) our default attitude toward theories that lack candor in a given test should be suspicion, but (2) the circumstance that a theory lacks candor in a testing situation does not preclude obtaining independent evidence for the auxiliary assumptions to which the theory is probabilistically relevant, and thereby eliminating the problem that lack of candor creates. Thus, Popper was right to think that lack of candor is a bad thing, but wrong to conclude that candor is a criterion of the scientificity of a theory. Seeing this requires recognition of some differences between intuitive relevance and probabilistic relevance, and proper appreciation of the notion of screening off and of the fact that probabilistic relevance is not transitive.

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Can a Theory-Laden Observation Test the Theory?

Cited by 49 publications

References 4 publications

Understanding Scientific Study via Process Modeling

Understanding Scientific Study via Process Modeling

Avoiding extreme risk before it occurs: A complexity science approach to incubation

Testability and Candor

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