Mathematical Psychology

This project investigates mathematical psychology's historical and philosophical foundations to clarify its distinguishing characteristics and relationships to adjacent fields. Through gathering primary sources, histories, and interviews with researchers, author Prof. Colin Allen - University of Pittsburgh [1, 2, 3] and his students Osman Attah, Brendan Fleig-Goldstein, Mara McGuire, and Dzintra Ullis have identified three central questions:

What makes the use of mathematics in mathematical psychology reasonably effective, in contrast to other sciences like physics-inspired mathematical biology or symbolic cognitive science?
How does the mathematical approach in mathematical psychology differ from other branches of psychology, like psychophysics and psychometrics?
What is the appropriate relationship of mathematical psychology to cognitive science, given diverging perspectives on aligning with this field?

Preliminary findings emphasize data-driven modeling, skepticism of cognitive science alignments, and early reliance on computation. They will further probe the interplay with cognitive neuroscience and contrast rational-analysis approaches. By elucidating the motivating perspectives and objectives of different eras in mathematical psychology's development, they aim to understand its past and inform constructive dialogue on its philosophical foundations and future directions. This project intends to provide a conceptual roadmap for the field through integrated history and philosophy of science.

The Project: Integrating History and Philosophy of Mathematical Psychology

This project aims to integrate historical and philosophical perspectives to elucidate the foundations of mathematical psychology. As Norwood Hanson stated, history without philosophy is blind, while philosophy without history is empty. The goal is to find a middle ground between the contextual focus of history and the conceptual focus of philosophy.

The team acknowledges that all historical accounts are imperfect, but some can provide valuable insights. The history of mathematical psychology is difficult to tell without centering on the influential Stanford group. Tracing academic lineages and key events includes part of the picture, but more context is needed to fully understand the field's development.

The project draws on diverse sources, including research interviews, retrospective articles, formal histories, and online materials. More interviews and research will further flesh out the historical and philosophical foundations. While incomplete, the current analysis aims to identify important themes, contrasts, and questions that shaped mathematical psychology's evolution. Ultimately, the goal is an integrated historical and conceptual roadmap to inform contemporary perspectives on the field's identity and future directions.

The Rise of Mathematical Psychology

The history of efforts to mathematize psychology traces back to the quantitative imperative stemming from the Galilean scientific revolution. This imprinted the notion that proper science requires mathematics, leading to "physics envy" in other disciplines like psychology.

Many early psychologists argued psychology needed to become mathematical to be scientific. However, mathematizing psychology faced complications absent in the physical sciences. Objects in psychology were not readily present as quantifiable, provoking heated debates on whether psychometric and psychophysical measurements were meaningful.

Nonetheless, the desire to develop mathematical psychology persisted. Different approaches grappled with determining the appropriate role of mathematics in relation to psychological experiments and data. For example, Herbart favored starting with mathematics to ensure accuracy, while Fechner insisted experiments must come first to ground mathematics.

Tensions remain between data-driven versus theory-driven mathematization of psychology. Contemporary perspectives range from psychometric and psychophysical stances that foreground data to measurement-theoretical and computational approaches that emphasize formal models.

Elucidating how psychologists negotiated to apply mathematical methods to an apparently resistant subject matter helps reveal the evolving role and place of mathematics in psychology. This historical interplay shaped the emergence of mathematical psychology as a field.

The Distinctive Mathematical Approach of Mathematical Psychology

What sets mathematical psychology apart from other branches of psychology in its use of mathematics?

Several key aspects stand out:

Advocating quantitative methods broadly. Mathematical psychology emerged partly to push psychology to embrace quantitative modeling and mathematics beyond basic statistics.
Drawing from diverse mathematical tools. With greater training in mathematics, mathematical psychologists utilize more advanced and varied mathematical techniques like topology and differential geometry.
Linking models and experiments. Mathematical psychologists emphasize tightly connecting experimental design and statistical analysis, with experiments created to test specific models.
Favoring theoretical models. Mathematical psychology incorporates "pure" mathematical results and prefers analytic, hand-fitted models over data-driven computer models.
Seeking general, cumulative theory. Unlike just describing data, mathematical psychology aspires to abstract, general theory supported across experiments, cumulative progress in models, and mathematical insight into psychological mechanisms.

So while not unique to mathematical psychology, these key elements help characterize how its use of mathematics diverges from adjacent fields like psychophysics and psychometrics. Mathematical psychology carved out an identity embracing quantitative methods but also theoretical depth and broad generalization.

Situating Mathematical Psychology Relative to Cognitive Science

What is the appropriate perspective on mathematical psychology's relationship to cognitive psychology and cognitive science? While connected historically and conceptually, essential distinctions exist.

Mathematical psychology draws from diverse disciplines that are also influential in cognitive science, like computer science, psychology, linguistics, and neuroscience. However, mathematical psychology appears more skeptical of alignments with cognitive science.

For example, cognitive science prominently adopted the computer as a model of the human mind, while mathematical psychology focused more narrowly on computers as modeling tools.

Additionally, mathematical psychology seems to take a more critical stance towards purely simulation-based modeling in cognitive science, instead emphasizing iterative modeling tightly linked to experimentation.

Overall, mathematical psychology exhibits significant overlap with cognitive science but strongly asserts its distinct mathematical orientation and modeling perspectives. Elucidating this complex relationship remains an ongoing project, but preliminary analysis suggests mathematical psychology intentionally diverged from cognitive science in its formative development.

This establishes mathematical psychology's separate identity while retaining connections to adjacent disciplines at the intersection of mathematics, psychology, and computation.

Looking Ahead: Open Questions and Future Research

This historical and conceptual analysis of mathematical psychology's foundations has illuminated key themes, contrasts, and questions that shaped the field's development. Further research can build on these preliminary findings.

Additional work is needed to flesh out the fuller intellectual, social, and political context driving the evolution of mathematical psychology. Examining the influences and reactions of key figures will provide a richer picture.

Ongoing investigation can probe whether the identified tensions and contrasts represent historical artifacts or still animate contemporary debates. Do mathematical psychologists today grapple with similar questions on the role of mathematics and modeling?

Further analysis should also elucidate the nature of the purported bidirectional relationship between modeling and experimentation in mathematical psychology. As well, clarifying the diversity of perspectives on goals like generality, abstraction, and cumulative theory-building would be valuable.

Finally, this research aims to spur discussion on philosophical issues such as realism, pluralism, and progress in mathematical psychology models. Is the accuracy and truth value of models an important consideration or mainly beside the point? And where is the field headed - towards greater verisimilitude or an indefinite balancing of complexity and abstraction?

By spurring reflection on this conceptual foundation, this historical and integrative analysis hopes to provide a roadmap to inform constructive dialogue on mathematical psychology's identity and future trajectory.

The SDTEST^®

The SDTEST^® is a simple and fun tool to uncover our unique motivational values that use mathematical psychology of varying complexity.

The SDTEST^® helps us better understand ourselves and others on this lifelong path of self-discovery.

Here are reports of polls which SDTEST^® makes:

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Below you can read an abridged version of the results of our VUCA poll “Fears“. The full version of the results is available for free in the FAQ section after login or registration.

Kutya

Charts Kuwirirana

VUCA

Critical kukosha kuwirirana coefficient

Zvakajairika kugoverwa, naWilliam Sealy Gosset (Mudzidzi) r = 0.033

Isiri kugoverwa, nemapfumo r = 0.0013

Ratidza chete mhinduro > r = 0.033

Kugovera	Zvisina kujairika	Zvisina kujairika	Zvisina kujairika	Zvakajairika	Zvakajairika	Zvakajairika	Zvakajairika	Zvakajairika
Mibvunzo yese Mibvunzo yese Kutya kwangu kukuru kuri
Kutya kwangu kukuru kuri
Answer 1	-	Vasina simba 0.0559	Vasina simba 0.0315	Kushaya simba -0.0170	Vasina simba 0.0920	Vasina simba 0.0294	Kushaya simba -0.0124	Kushaya simba -0.1539
Answer 2	-	Vasina simba 0.0229	Kushaya simba -0.0002	Kushaya simba -0.0448	Vasina simba 0.0636	Vasina simba 0.0445	Vasina simba 0.0134	Kushaya simba -0.0939
Answer 3	-	Kushaya simba -0.0032	Kushaya simba -0.0121	Kushaya simba -0.0416	Kushaya simba -0.0462	Vasina simba 0.0466	Vasina simba 0.0788	Kushaya simba -0.0195
Answer 4	-	Vasina simba 0.0438	Vasina simba 0.0348	Kushaya simba -0.0195	Vasina simba 0.0153	Vasina simba 0.0300	Vasina simba 0.0207	Kushaya simba -0.0980
Answer 5	-	Vasina simba 0.0304	Vasina simba 0.1282	Vasina simba 0.0135	Vasina simba 0.0734	Kushaya simba -0.0013	Kushaya simba -0.0200	Kushaya simba -0.1757
Answer 6	-	Kushaya simba -0.0002	Vasina simba 0.0082	Kushaya simba -0.0627	Kushaya simba -0.0083	Vasina simba 0.0193	Vasina simba 0.0831	Kushaya simba -0.0315
Answer 7	-	Vasina simba 0.0126	Vasina simba 0.0381	Kushaya simba -0.0687	Kushaya simba -0.0243	Vasina simba 0.0469	Vasina simba 0.0642	Kushaya simba -0.0515
Answer 8	-	Vasina simba 0.0698	Vasina simba 0.0848	Kushaya simba -0.0327	Vasina simba 0.0148	Vasina simba 0.0345	Vasina simba 0.0134	Kushaya simba -0.1365
Answer 9	-	Vasina simba 0.0668	Vasina simba 0.1676	Vasina simba 0.0083	Vasina simba 0.0693	Kushaya simba -0.0131	Kushaya simba -0.0516	Kushaya simba -0.1818
Answer 10	-	Vasina simba 0.0782	Vasina simba 0.0753	Kushaya simba -0.0204	Vasina simba 0.0247	Vasina simba 0.0342	Kushaya simba -0.0131	Kushaya simba -0.1304
Answer 11	-	Vasina simba 0.0578	Vasina simba 0.0532	Kushaya simba -0.0096	Vasina simba 0.0087	Vasina simba 0.0195	Vasina simba 0.0311	Kushaya simba -0.1196
Answer 12	-	Vasina simba 0.0390	Vasina simba 0.1037	Kushaya simba -0.0358	Vasina simba 0.0358	Vasina simba 0.0250	Vasina simba 0.0299	Kushaya simba -0.1520
Answer 13	-	Vasina simba 0.0644	Vasina simba 0.1048	Kushaya simba -0.0448	Vasina simba 0.0268	Vasina simba 0.0417	Vasina simba 0.0178	Kushaya simba -0.1600
Answer 14	-	Vasina simba 0.0712	Vasina simba 0.1021	Kushaya simba -0.0007	Kushaya simba -0.0088	Kushaya simba -0.0011	Vasina simba 0.0088	Kushaya simba -0.1169
Answer 15	-	Vasina simba 0.0557	Vasina simba 0.1365	Kushaya simba -0.0423	Vasina simba 0.0177	Kushaya simba -0.0162	Vasina simba 0.0224	Kushaya simba -0.1179
Answer 16	-	Vasina simba 0.0591	Vasina simba 0.0273	Kushaya simba -0.0386	Kushaya simba -0.0400	Vasina simba 0.0653	Vasina simba 0.0284	Kushaya simba -0.0708

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[1] https://twitter.com/wileyprof

[2] https://colinallen.dnsalias.org

[3] https://philpeople.org/profiles/colin-allen

2023.10.13

Valerii Kosenko

Chigadzirwa muridzi saas pet projekiti sdtest®

Valerii aive akakodzera semagariro pedagogue-psychologist muna1993 uye kubva paakashandisa ruzivo rwake mune Project manejimendi.
Valerii akawana degree raTenzi uye chirongwa uye chirongwa chezvirongwa
Valerii akatora akasiyana-siyana ehupamhi ehupamhi bvunzo uye akashandisa ruzivo rwake uye ruzivo rwekuziva iyo yazvino shanduro yeSdtest.
Valeri ndiye munyori wekuongorora kusagadzikana kweV.u.c.C.a. Pfungwa ichishandisa Spiral Dynamics uye manhamba emasvomhu muPsychology, anopfuura makumi maviri emapauro epasi rose.

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