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:

1) گذريل مهيني ۾ اهلڪارن جي حوالي سان ڪمپنين جا عمل (ها / نه)

2) گذريل مهيني ۾ اهلڪارن جي حوالي سان ڪمپنين جا ڪارناما (حقيقت٪ ۾)

3) خوفناڪ

4) منهنجي ملڪ کي منهن ڏيڻ وارا وڏا مسئلا

5) ڪامياب ٽيمون تعمير ڪرڻ وقت ڪهڙيون خوبيون ۽ صلاحيتون ۽ صلاحيتون استعمال ڪنديون آهن؟

6) گوگل. عنصر جيڪي ٽيم جي اثر تي اثر انداز ٿين ٿا

7) نوڪري ڳوليندڙن جا بنيادي ترجيحات

8) باس کي هڪ عظيم اڳواڻ ڇا ٺاهيندو آهي؟

9) ماڻهن کي ڪم تي ڪامياب ڇا بڻائي ٿو؟

10) ڇا توهان دور دراز ڪم ڪرڻ لاء گهٽ ادائيگي حاصل ڪرڻ لاء تيار آهيو؟

11) ڇا ايجنسزم موجود آهي؟

12) ڪيريئر ۾ ايجنٽ

13) عمر ۾ عمر

14) عمر جو سبب

15) ماڻهن کي ڇو ڇڏي ڏيو (انا جي اهم)

16) ڀروسو (#WVS)

17) آڪسفورڊ خوشي سروي

18) نفسياتي خوشحالي

19) توهان جو ايندڙ دلچسپ موقعو ڪٿي هوندو؟

20) توهان پنهنجي ذهني صحت جو خيال رکڻ لاء هن هفتي ڇا ڪندا؟

21) مان پنهنجي ماضي، موجوده يا مستقبل بابت سوچيندي رهندو آهيان

22) ميريڪريسي

23) مصنوعي ذهانت ۽ تهذيب جو خاتمو

24) ماڻهو ڇو طنز ڪندا آهن؟

25) خود اعتمادي جي تعمير ۾ صنف جو فرق (IFD يڪينبچ)

26) Xing.com ثقافت جو جائزو

27) پيٽرڪ لينسڪيسي جو "هڪ ٽيم جي پنج ڊفيڪشن"

28) ايمانداري آهي ...

29) نوڪري جي آڇ چونڊڻ ۾ ان لاء ڇا ضروري آهي؟

30) ماڻهو ڇو تبديلي جي مزاحمت ڪن ٿا (سيوبي مچلي ذريعي)

31) توهان پنهنجي جذبات کي ڪيئن منظم ڪيو؟ (نالالما ايم اي ايف اي ايم پاران)

32) 21 صلاحيتون جيڪي توهان کي هميشه لاء ادا ڪنديون آهن (جريميا ٽيو / 赵汉昇 طرفان)

33) حقيقي آزادي آهي ...

34) ٻين سان اعتماد پيدا ڪرڻ جا 12 طريقا (جسٽن رائيٽ ذريعي)

35) هڪ باصلاحيت ملازم جي خاصيتون (ٽيلنٽ مينيجمينٽ انسٽيٽيوٽ طرفان)

36) توهان جي ٽيم کي متحرڪ ڪرڻ لاء 10 ڪيچ

37) ضمير جو الجبرا (ولاديمير ليفيبري طرفان)

38) مستقبل جا ٽي الڳ امڪان (ڊاڪٽر ڪليئر ڊبليو قبرز پاران)

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.

خوفناڪ

چارٽس باهمي

VUCA

رابطي واري گنجائش جي نازڪ قدر

عام تقسيم، وليم سامونڊي گيسس (شاگرد) طرفان r = 0.033

غير معمولي تقسيم، سپيرمن طرفان r = 0.0013

صرف نتيجا ڏيکاريو > r = 0.033

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

ذيشان فضيلت ڏانھن موڪليو

هي ڪارڪردگي توهان جي پنهنجي VUCA چونڊن ۾ دستياب هوندي

ٺيڪ آ ٺيڪ ن

You can not only just create your poll in the گالا «V.U.C.A ڪ ڪاريگر» (with a unique link and your logo) but also you can earn money by selling its results in the گالا «جو هلنگ جو دڪان», as already the authors of polls.

If you participated in VUCA polls, you can see your results and compare them with the overall polls results, which are constantly growing, in your personal account after purchasing گالا «منهنجي SDT»

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

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

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

2023.10.13

ويلري ڪوکوڪو

مصنوعات جي مالڪ ساس پالتو پروجيڪٽ SDSTST®

وليري 1993 ۾ سماجي پيڊ اوگولوججسٽ- نفسيات جي ماهر طور قابليت ڪئي ۽ منصوبي جي انتظام ۾ پنهنجو علم لاڳو ڪيو ويو آهي.
وليري ماسٽر جي ڊگري حاصل ڪئي ۽ پروجيڪٽ ۽ پروگرام جو مئنيجر ايسٽمينٽ قابليت حاصل ڪئي. هن جي ماسٽر جي پروگرام دوران، هو پروفيسرز گيٽس جيوٽس اسٽرلينٽ فئڪٽڪز سان واقف ٿي ويو.
وليري مختلف سرپل ڊائنامڪس ٽيسٽ ورتو ۽ SDST جو موجوده نسخو کي ترتيب ڏيڻ لاء هن جو علم ۽ تجربو استعمال ڪيو.
وليري V.u.ca.a جي غير يقيني صورتحال کي ڳولڻ جو مصنف آهي. نفسيات ۾ 20 انٽرنيشنل پولز ۾ سرپل ڊائنميٽڪ شماريات استعمال ڪندي تصور، 20 بين الاقوامي پولز کان وڌيڪ.

هن پوسٽ کي آهي 0 سممريون

جواب ڏيو

جواب رد ڪريو

پنهنجو تبصرو ڇڏي ڏيو