Maxwell on the Method of Physical Analogy

Turner, Joseph

doi:10.1093/bjps/vi.23.226

Cited by 29 publications

(19 citation statements)

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“…110–115) care in structuring his models in the same mathematical form as Maxwell's analysis of force, mass, and acceleration. By deliberately requiring models of this form, Rasch employs Maxwell's own method of analogy (Turner, 1955; Nersessian, 2002) and enables us to apply it, as Maxwell did, in setting up individual-level tests of hypotheses about potential causal relations among the model parameters (Fisher, 2010). …”

Section: Distinguishing Features Of Causal Rasch Modelsmentioning

confidence: 99%

Causal Rasch models

et al. 2013

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Rasch's unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained.

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Section: Distinguishing Features Of Causal Rasch Modelsmentioning

confidence: 99%

Causal Rasch models

et al. 2013

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“…We treat optical flow as a vector field for each frame. Our interest points are those points that have a curl [26] magnitude greater than a threshold. We also experimented with divergence, but the empirical results were not satisfactory.…”

Section: Proposed Algorithmmentioning

confidence: 99%

A Flow-based Interest Point Detector for Action Recognition in Videos

Yadav

Sethi

2014

Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing

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Video interest points, in combination with local appearance descriptors, are used for human action recognition. Most of the previously proposed video interest point detectors are straightforward extensions of some image interest point detector or the other. These methods treat the temporal dimension (inter-frame) similar to the spatial dimensions (intra-frame). We argue that certain unique properties of the temporal dimension beg a different treatment. We propose an interest point detector based on vector calculus of optical flow to take advantage of the unique properties of the temporal dimension. Compared to previously proposed methods, the proposed method exhibits higher repeatability (robustness) and lower displacement (stability) of interest points under two common video transformations testedvideo compression and spatial scaling. It also shows competitive action recognition performance when paired with appropriate feature descriptors in a bag of features model.

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“…10 Por sua vez, a distinção "observacional/não-observacional" pode continuar a ser pensada, seja como uma questão epistemológica (cf. Carman & Fernández, 2004) ou, como sugere Van Fraassen, como uma questão empírica, que nem mesmo pertence ao escopo da filosofia (Van Fraassen, 2007[1980, Cap. 3, § 7).…”

Section: Modelos Instanciais E Modelos Representacionaisunclassified

“…À luz das relações consideradas acima, podemos imaginar que a relação fundamental na adequação empírica das teorias científicas seja a existência de isomorfismo entre o modelo teórico e o modelo de dados (cf. Van Fraassen, 2007[1980. Notemos que o isomorfismo pode ser uma relação forte demais para ser exigida das estruturas, no caso da adequação empírica.…”

Section: Figura 4 a Relação De Modelagem Tipo I Em Termos Da Relaçãounclassified

Estruturas conceituais e estratégias de investigação: modelos representacionais e instanciais, analogias e correspondência

Bezerra¹

2011

Sci. stud.

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São discutidas, neste artigo, determinadas estratégias de investigação científica que têm em comum as características de estar fundadas sobre as noções de modelo e de depender de um contraponto entre duas ou mais estruturas. São focalizadas três dessas estratégias científicas. Analisa-se, primeiramente, a modelagem, tal como entendida usualmente na ciência. Para isso, distinguem-se duas noções de modelo: a noção lógica ou instancial e a noção prototeórica ou representacional. Ao mesmo tempo em que são assinaladas as diferenças entre as duas acepções do termo, procura-se também compreender de que maneira elas estão relacionadas. Em particular, para investigar a relação (entre estruturas e realidade) de modelagem representacional é preciso invocar a relação (entre estruturas e estruturas) de modelagem lógica. A análise dos modelos também contribui para elucidar a relação de adequação empírica entre as teorias científicas e os dados, por meio da noção de subestrutura empírica ou modelo de dados. São consideradas, em segundo lugar, as analogias. O seu funcionamento é aqui analisado em termos de modelos e isomorfismos parciais, o que permite capturar a ideia de uma tradução dos problemas e de suas soluções em domínios de investigação diferentes. Destaca-se o papel importante desempenhado pelas analogias no pensamento científico de Maxwell (que também atribuía lugar de destaque aos modelos). Em terceiro lugar, discute-se o princípio de correspondência, que historicamente desempenhou um papel notável na primeira fase da teoria quântica. São identificadas duas formas, de teor diferente, que o princípio assumiu na teoria quântica, sendo ambas elucidadas em termos de modelos. Para contextualizar a discussão sobre o princípio de correspondência, e também para exemplificar as características dos modelos representacionais, dedica-se aqui uma atenção especial ao modelo atômico de Bohr-Sommerfeld.
In the present article some strategies of scientific inquiry are discussed which have a pair of features in common: first, they are based on the notions of model, and second, they depend on a counterpoint between two or more structures. Three strategies of this kind are considered. First, I consider modeling in the usual scientific sense. In order to do this, one distinguishes between two notions of model: the logical or instantial one, and the proto-theoretical or representational one. While the differences between both senses of the term are highlighted, an attempt is also made to understand the sense in which the two are related to one another. In particular, in order to investigate the structure-reality relationship of representational modeling, one needs to invoke the structure-structure relationship of logical modeling. The analysis of models contributes also to clarify the relational nature of empirical adequacy between scientific theories and data, through the notion of empirical substructure or model of data. Second, analogies are considered. Their operation is analyzed here in terms of models and partial isomorphisms, whi...

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Maxwell on the Method of Physical Analogy

Cited by 29 publications

References 0 publications

Causal Rasch models

Causal Rasch models

A Flow-based Interest Point Detector for Action Recognition in Videos

Estruturas conceituais e estratégias de investigação: modelos representacionais e instanciais, analogias e correspondência

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