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Journal articles on the topic 'Theory and Models'

Author: Grafiati

Published: 10 March 2023

Last updated: 19 July 2025

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1

Bennardo, Giovanni. "Cultural Models Theory." Anthropology News 59, no. 4 (2018): e139-e142. http://dx.doi.org/10.1111/an.919.

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2

Lewis, Robert. "Neurobiological Theory and Models." Clinical Journal of the International Institute for Bioenergetic Analysis 22, no. 1 (2012): 109–26. http://dx.doi.org/10.30820/0743-4804-2012-22-109.

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This paper examines the clinical relevance of recent neuroscience data to the practice of bioenergetic analysis. I conclude that the nonverbal, bodily basis of our approach is affirmed by the evolving picture of a right-brain-to right-brain infant-caregiver dialogue engraving our attachment experience into the right limbic system as a model of relationships to come. But I also conclude that, for most of us, the neurobiological data does not help us in real time to be present with our patient in the clinical encounter. Two clinical vignettes illustrate both the above perspective and the continuing relevance of our basic Reichian/Lowenian model of our patient as the trillion-celled amoeba.

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3

Forbes, T. G., J. A. Linker, J. Chen, et al. "CME Theory and Models." Space Science Reviews 123, no. 1-3 (2006): 251–302. http://dx.doi.org/10.1007/s11214-006-9019-8.

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4

ŠINDELÁŘ, JAN. "MODELS IN GNOSTICAL THEORY." International Journal of General Systems 21, no. 4 (1993): 365–78. http://dx.doi.org/10.1080/03081079308945087.

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5

Erdem, Tülin, Kannan Srinivasan, Wilfred Amaldoss, et al. "Theory-Driven Choice Models." Marketing Letters 16, no. 3-4 (2005): 225–37. http://dx.doi.org/10.1007/s11002-005-5887-z.

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6

Babel, L. V., and D. Karssenberg. "Hydrological models are mediating models." Hydrology and Earth System Sciences Discussions 10, no. 8 (2013): 10535–63. http://dx.doi.org/10.5194/hessd-10-10535-2013.

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Abstract. Despite the increasing role of models in hydrological research and decision-making processes, only few accounts of the nature and function of models exist in hydrology. Earlier considerations have traditionally been conducted while making a clear distinction between physically-based and conceptual models. A new philosophical account, primarily based on the fields of physics and economics, transcends classes of models and scientific disciplines by considering models as "mediators" between theory and observations. The core of this approach lies in identifying models as (1) being only partially dependent on theory and observations, (2) integrating non-deductive elements in their construction, and (3) carrying the role of instruments of scientific enquiry about both theory and the world. The applicability of this approach to hydrology is evaluated in the present article. Three widely used hydrological models, each showing a different degree of apparent physicality, are confronted to the main characteristics of the "mediating models" concept. We argue that irrespective of their kind, hydrological models depend on both theory and observations, rather than merely on one of these two domains. Their construction is additionally involving a large number of miscellaneous, external ingredients, such as past experiences, model objectives, knowledge and preferences of the modeller, as well as hardware and software resources. We show that hydrological models convey the role of instruments in scientific practice by mediating between theory and the world. It results from these considerations that the traditional distinction between physically-based and conceptual models is necessarily too simplistic and refers at best to the stage at which theory and observations are steering model construction. The large variety of ingredients involved in model construction would deserve closer attention, for being rarely explicitly presented in peer-reviewed literature. We believe that devoting more importance to identifying and communicating on the many factors involved in model development might increase transparency of model building.

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7

Girardello, Paolo, Orietta Nicolis, and Giovanni Tondini. "Comparing Conditional Variance Models: Theory and Empirical Evidence." Multinational Finance Journal 7, no. 3/4 (2003): 177–206. http://dx.doi.org/10.17578/7-3/4-4.

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8

CHEN, Guanyu, and Ping CHEN. "Explanatory item response theory models: Theory and application." Advances in Psychological Science 27, no. 5 (2019): 937. http://dx.doi.org/10.3724/sp.j.1042.2019.00937.

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9

Brzezińska, Justyna. "Item response theory models in the measurement theory." Communications in Statistics - Simulation and Computation 49, no. 12 (2018): 3299–313. http://dx.doi.org/10.1080/03610918.2018.1546399.

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10

Nakamori, Yoshiteru, and Shigemasa Suganuma. "Landscape Theory and Extension Models." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 16, no. 1 (2004): 3–7. http://dx.doi.org/10.3156/jsoft.16.3.

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11

Snell, Joyce, and B. Jorgensen. "The Theory of Linear Models." Journal of the Royal Statistical Society. Series A (Statistics in Society) 158, no. 1 (1995): 195. http://dx.doi.org/10.2307/2983426.

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12

Hey, John D., Marcel Boyer, and Richard E. Kihlstrom. "Bayesian Models in Economic Theory." Economic Journal 95, no. 377 (1985): 224. http://dx.doi.org/10.2307/2233492.

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13

Enayat, Ali. "Leibnizian models of set theory." Journal of Symbolic Logic 69, no. 3 (2004): 775–89. http://dx.doi.org/10.2178/jsl/1096901766.

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Abstract.A model is said to be Leibnizian if it has no pair of indiscernibles. Mycielski has shown that there is a first order axiom LM (the Leibniz-Mycielski axiom) such that for any completion T of Zermelo-Fraenkel set theory ZF. T has a Leibnizian model if and only if T proves LM. Here we prove:Theorem A. Every complete theory T extending ZF + LM has nonisomorphic countable Leibnizian models.Theorem B. If κ is a prescribed definable infinite cardinal ofa complete theory T extending ZF + V = OD, then there are nonisomorphic Leibnizian models of T of power ℵ1such thatis ℵ1-like.Theorem C. Every complete theory T extendingZF + V = ODhas nonisomorphic ℵ1-like Leibnizian models.

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14

Mayne, John. "Useful Theory of Change Models." Canadian Journal of Program Evaluation 30, no. 2 (2015): 119–42. http://dx.doi.org/10.3138/cjpe.230.

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15

Taylor, Peter. "Revising Models and Generating Theory." Oikos 54, no. 1 (1989): 121. http://dx.doi.org/10.2307/3565906.

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16

Wacquant, Loic J. D. "Heuristic Models in Marxian Theory." Social Forces 64, no. 1 (1985): 17. http://dx.doi.org/10.2307/2578970.

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17

von Glehn, Tamara. "Polynomial Models of Type Theory." Electronic Proceedings in Theoretical Computer Science 275 (July 10, 2018): 1. http://dx.doi.org/10.4204/eptcs.275.1.

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18

Seeber, G. U. H., and B. Jorgensen. "The Theory of Linear Models." Journal of the American Statistical Association 90, no. 429 (1995): 385. http://dx.doi.org/10.2307/2291168.

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19

Purisima, Enrico, and Traian Sulea. "Solvation Models: Theory and Validation." Current Pharmaceutical Design 20, no. 20 (2014): 3266–80. http://dx.doi.org/10.2174/13816128113199990599.

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20

Kalashnikova, Yu S. "Heavy Quarkonia: Models and Theory." Ядерная физика 76, no. 11 (2013): 1448–54. http://dx.doi.org/10.7868/s0044002713100085.

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21

Bohning, D., and B. Jorgensen. "The Theory of Linear Models." Biometrics 51, no. 2 (1995): 791. http://dx.doi.org/10.2307/2532966.

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22

Enayat, Ali. "Counting models of set theory." Fundamenta Mathematicae 174, no. 1 (2002): 23–47. http://dx.doi.org/10.4064/fm174-1-2.

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23

Jijyan, Anahit, and Romik Qocharyan. "From Empiric Models to Theory." WISDOM 1, no. 1 (2013): 105. http://dx.doi.org/10.24234/wisdom.v1i1.20.

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24

Ryan, Sarah M. "Stochastic Models in Queueing Theory." Journal of the American Statistical Association 100, no. 469 (2005): 350–51. http://dx.doi.org/10.1198/jasa.2005.s4.

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25

Vonesh, Edward F. "Mixed Models: Theory and Applications." Journal of the American Statistical Association 101, no. 476 (2006): 1724–26. http://dx.doi.org/10.1198/jasa.2006.s146.

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26

Anastopoulos, Charis, and Ntina Savvidou. "Minisuperspace models in histories theory." Classical and Quantum Gravity 22, no. 9 (2005): 1841–66. http://dx.doi.org/10.1088/0264-9381/22/9/023.

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27

Grigorian, Sergey. "Minisuperspace models in M-theory." Classical and Quantum Gravity 24, no. 20 (2007): 4881–913. http://dx.doi.org/10.1088/0264-9381/24/20/001.

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28

Wagner, Wolfgang. "Stochastic models in kinetic theory." Physics of Fluids 23, no. 3 (2011): 030602. http://dx.doi.org/10.1063/1.3558866.

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29

Rueger, Alexander. "Perspectival Models and Theory Unification." British Journal for the Philosophy of Science 56, no. 3 (2005): 579–94. http://dx.doi.org/10.1093/bjps/axi128.

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30

Traulsen, Arne. "Biological models in game theory." Journal of Statistical Theory and Practice 10, no. 2 (2016): 472–74. http://dx.doi.org/10.1080/15598608.2016.1172462.

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31

Goidel, Robert K., Todd G. Shields, and Mark Peffley. "Priming Theory and Ras Models." American Politics Quarterly 25, no. 3 (1997): 287–318. http://dx.doi.org/10.1177/1532673x9702500303.

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32

Kalashnikova, Yu S. "Heavy quarkonia: Models and theory." Physics of Atomic Nuclei 76, no. 12 (2013): 1525–32. http://dx.doi.org/10.1134/s1063778813220018.

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33

Teitz, Michael B. "REGIONAL THEORY AND REGIONAL MODELS." Papers in Regional Science 9, no. 1 (2005): 35–50. http://dx.doi.org/10.1111/j.1435-5597.1962.tb01824.x.

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34

Fawcett, Jacqueline. "Conceptual Models and Theory Development." Journal of Obstetric, Gynecologic & Neonatal Nursing 17, no. 6 (1988): 400–403. http://dx.doi.org/10.1111/j.1552-6909.1988.tb00465.x.

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35

Jackson, R. R. P., W. M. Gregory, and B. G. Birkhead. "Queueing Theory Models in Practice." IFAC Proceedings Volumes 18, no. 5 (1985): 221–23. http://dx.doi.org/10.1016/s1474-6670(17)60562-7.

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36

Bachant, Janet Lee, Arthur A. Lynch, and Arnold David Richards. "Relational models in psychoanalytic theory." Psychoanalytic Psychology 12, no. 1 (1995): 71–87. http://dx.doi.org/10.1037/h0079599.

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37

Seidenberg, Mark S. "Connectionist Models and Cognitive Theory." Psychological Science 4, no. 4 (1993): 228–35. http://dx.doi.org/10.1111/j.1467-9280.1993.tb00266.x.

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Connectionist models have come to play an important role in cognitive science and in cognitive neuroscience, yet their role in explaining behavior is not necessarily obvious and has generated considerable debate. Connectionism is a body of tools and ideas that can be used in different ways. It can be treated as a form of simulation modeling in which the goal is to implement preexisting theories. In this approach, connectionist models function as a kind of statistical tool, a way of analyzing a complex set of data. Connectionism can also be seen as providing a small set of general theoretical principles that apply in a variety of domains. Construed in this way, it contributes to the development of theories that are explanatory, not merely descriptive.

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38

Borowiak, Dale. "The Theory of Linear Models." Technometrics 37, no. 2 (1995): 228–29. http://dx.doi.org/10.1080/00401706.1995.10484307.

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39

Sen, Ananda. "The Theory of Dispersion Models." Technometrics 41, no. 2 (1999): 177–78. http://dx.doi.org/10.1080/00401706.1999.10485652.

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40

Mărginean, Diana. "Remarcable Models of Potential Theory." Procedia Technology 22 (2016): 934–37. http://dx.doi.org/10.1016/j.protcy.2016.01.091.

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41

Vaxevanou, Anthi, and Nikolaos Konstantopoulos. "Models Referring to Outsourcing Theory." Procedia - Social and Behavioral Sciences 175 (February 2015): 572–78. http://dx.doi.org/10.1016/j.sbspro.2015.01.1239.

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42

Ennes, Isabel P., Carlos Lozano, Stephen G. Naculich, and Howard J. Schnitzer. "Elliptic models and M-theory." Nuclear Physics B 576, no. 1-3 (2000): 313–46. http://dx.doi.org/10.1016/s0550-3213(00)00131-0.

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43

Jiang, Jing, Tianjun Li, Dimitri V. Nanopoulos, and Dan Xie. "Flipped models from F-theory." Nuclear Physics B 830, no. 1-2 (2010): 195–220. http://dx.doi.org/10.1016/j.nuclphysb.2009.12.028.

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44

ter Meulen, Alice G. B. "Situation theory and mental models." Behavioral and Brain Sciences 16, no. 2 (1993): 358–59. http://dx.doi.org/10.1017/s0140525x00030545.

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45

Lukash, V. N. "Cosmological models: Theory and observations." Advances in Space Research 31, no. 2 (2003): 409–15. http://dx.doi.org/10.1016/s0273-1177(02)00730-5.

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46

Grosse, Harald, and Karl-Georg Schlesinger. "Spinfoam models for M-theory." Physics Letters B 528, no. 1-2 (2002): 106–10. http://dx.doi.org/10.1016/s0370-2693(02)01198-x.

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47

Ramos, J. I. "Stochastic Models in Queueing Theory." Applied Mathematical Modelling 17, no. 5 (1993): 280. http://dx.doi.org/10.1016/0307-904x(93)90052-i.

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48

Makarieva, Anastassia M., Victor G. Gorshkov, and Bai-Lian Li. "Ontogenetic growth: models and theory." Ecological Modelling 176, no. 1-2 (2004): 15–26. http://dx.doi.org/10.1016/j.ecolmodel.2003.09.037.

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49

Alexandrov, A. S., A. D. Mironov, and A. Yu Morozov. "M-theory of matrix models." Theoretical and Mathematical Physics 150, no. 2 (2007): 153–64. http://dx.doi.org/10.1007/s11232-007-0011-6.

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50

Demianski, M., R. De Ritis, G. Platania, P. Scudellaro, and C. Stornaiolo. "Inflationary models in ECSK theory." Physics Letters A 116, no. 1 (1986): 13–16. http://dx.doi.org/10.1016/0375-9601(86)90347-6.

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