mx agcrprod
DESCRIPTION
rqwTRANSCRIPT
![Page 1: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/1.jpg)
Aging and Creative Productivity
Is There an Age Decrement or Not?
![Page 2: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/2.jpg)
Brief history: Antiquity of topic
Quételet (1835) Beard (1874) Lehman (1953) Dennis (1966) Simonton (1975, 1988, 1997, 2000,
2004)
![Page 3: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/3.jpg)
Central findings: The typical age curve
Described by fitting an equation derived from a combinatorial model of the
creative process
![Page 4: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/4.jpg)
Henri Poincaré (1921):Ideas rose in crowds; I felt them collideuntil pairs interlocked, so to speak,making a stable combination.
[These ideas are like] the hooked atomsof Epicurus [that collide] like themolecules of gas in the kinematic theoryof gases [so that] their mutual impactsmay produce new combinations.
![Page 5: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/5.jpg)
p (t) = c (e – at – e – bt)where p (t) is productivity at career age t (in years),
e is the exponential constant (~ 2.718),
a the typical ideation rate for the domain (0 < a < 1),
b the typical elaboration rate for the domain (0 < b < 1),
c = abm/(b – a), where m is the individual’s creative potential (i.e. maximum number of publications in indefinite lifetime).
[N.B.: If a = b, then p (t) = a2mte – at]
![Page 6: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/6.jpg)
0 20 40 60Career Age
0.0
0.5
1.0
1.5
2.0P
rodu
ctiv
i ty
![Page 7: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/7.jpg)
Central findings: The typical age curve Rapid ascent (decelerating)
![Page 8: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/8.jpg)
0 20 40 60Career Age
0.0
0.5
1.0
1.5
2.0P
rod
uct
ivity
![Page 9: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/9.jpg)
Central findings: The typical age curve Rapid ascent (decelerating) Single peak
![Page 10: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/10.jpg)
0 20 40 60Career Age
0.0
0.5
1.0
1.5
2.0P
rodu
ctiv
i ty
![Page 11: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/11.jpg)
Central findings: The typical age curve Rapid ascent (decelerating) Single peak Gradual decline (asymptotic)
![Page 12: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/12.jpg)
0 20 40 60Career Age
0.0
0.5
1.0
1.5
2.0P
rodu
ctiv
i ty
![Page 13: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/13.jpg)
With correlations with published data between .95 and .99.
![Page 14: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/14.jpg)
Criticisms of findings:Is the age decrement real?
![Page 15: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/15.jpg)
Criticisms of findings:Is the age decrement real? Quality but not quantity?
![Page 16: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/16.jpg)
Criticisms of findings:Is the age decrement real? Quality but not quantity?
– But high correlation between two
![Page 17: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/17.jpg)
Criticisms of findings:Is the age decrement real? Quality but not quantity? Differential competition?
![Page 18: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/18.jpg)
Criticisms of findings:Is the age decrement real? Quality but not quantity? Differential competition?
– But survives statistical controls
![Page 19: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/19.jpg)
Criticisms of findings:Is the age decrement real? Quality but not quantity? Differential competition? Aggregation error?
![Page 20: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/20.jpg)
Criticisms of findings:Is the age decrement real? Quality but not quantity? Differential competition? Aggregation error?
– But persists at individual level
![Page 21: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/21.jpg)
e.g., the career of Thomas Edison
CEdison (t) = 2595(e - .044t - e - .058t)
r = .74
![Page 22: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/22.jpg)
0 10 20 30 40 50 60 70 80Career Age
0
100
200
300
400
500P
ate
nts
Predicted CountObserved Count
![Page 23: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/23.jpg)
However ...
![Page 24: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/24.jpg)
Complicating considerations
![Page 25: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/25.jpg)
Complicating considerations
Individual differences
![Page 26: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/26.jpg)
Complicating considerations
Individual differences– Creative potential (m in model)
![Page 27: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/27.jpg)
1 2 3 4 5 6 7 8 9 10 11 12
Decile
0.0
0.1
0.2
0.3
0.4
0.5
Pro
po
rtio
n
PsychologyChemistryInfantile ParalysisGeologyGerontology/Geriatrics
![Page 28: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/28.jpg)
In fact, 1) cross-sectional variation always appreciably greater than longitudinal variation2) the lower an individual’s productivity the more random the longitudinal distribution becomes
![Page 29: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/29.jpg)
Complicating considerations
Individual differences– Creative potential– Age at career onset (i.e., chronological age
at t = 0 in model)
![Page 30: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/30.jpg)
Hence, arises a two-dimensional typology of career trajectories
![Page 31: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/31.jpg)
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
High Creative Early Bloomers Low Creative Early Bloomers
High Creative Late Bloomers Low Creative Late Bloomers
f b l
f b l
f b l
f b l
![Page 32: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/32.jpg)
Complicating considerations
Individual differences Quantity-quality relation
![Page 33: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/33.jpg)
Complicating considerations
Individual differences Quantity-quality relation
– The equal-odds rule
![Page 34: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/34.jpg)
Complicating considerations
Individual differences Quantity-quality relation
– The equal-odds rule– Career landmarks
![Page 35: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/35.jpg)
Complicating considerations
Individual differences Quantity-quality relation
– The equal-odds rule– Career landmarks:
• First major contribution (f)
![Page 36: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/36.jpg)
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
High Creative Early Bloomers Low Creative Early Bloomers
High Creative Late Bloomers Low Creative Late Bloomers
f b l
f b l
f b l
f b l
![Page 37: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/37.jpg)
Complicating considerations
Individual differences Quantity-quality relation
– The equal-odds rule– Career landmarks:
• First major contribution (f)• Single best contribution (b)
![Page 38: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/38.jpg)
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
High Creative Early Bloomers Low Creative Early Bloomers
High Creative Late Bloomers Low Creative Late Bloomers
f b l
f b l
f b l
f b l
![Page 39: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/39.jpg)
Complicating considerations
Individual differences Quantity-quality relation
– The equal-odds rule– Career landmarks:
• First major contribution (f)• Single best contribution (b)• Last major contribution(l)
![Page 40: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/40.jpg)
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
2030405060708090Chronological Age
0
1
2
3
4
5
Cre
ativ
e Pr
o duc
tivity
High Creative Early Bloomers Low Creative Early Bloomers
High Creative Late Bloomers Low Creative Late Bloomers
f b l
f b l
f b l
f b l
![Page 41: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/41.jpg)
Journalist Alexander Woolcott reporting on G. B. Shaw:
“At 83 Shaw’s mind was perhaps not quite as good as it used to be.
It was still better than anyone else’s.”
![Page 42: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/42.jpg)
Complicating considerations
Individual differences Quantity-quality relation Inter-domain contrasts (a and b in
model)
![Page 43: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/43.jpg)
Complicating considerations
Individual differences Quantity-quality relation Inter-domain contrasts
– Differential decrements (0-100%)
![Page 44: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/44.jpg)
10 20 30 40 50 60 70 80Age Decade
0
10
20
30P
erc
en
t o
f To
tal L
ifet im
e O
ut p
ut
ARTISTSSCIENTISTSSCHOLARS
![Page 45: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/45.jpg)
Complicating considerations
Individual differences Quantity-quality relation Inter-domain contrasts
– Differential peaks and decrements – Differential landmark placements
![Page 46: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/46.jpg)
Astronomy
Biology
Chemistry
Geoscience
Mathematics
Medicine
Physics
Technology
DISCIPLINE
20
30
40
50
60
Chr
ono
l og i
c al A
g e
Last Major ContributionBest ContributionFirst Major Contribution
![Page 47: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/47.jpg)
Complicating considerations
Individual differences Quantity-quality relation Inter-domain contrasts Impact of extraneous factors
![Page 48: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/48.jpg)
Complicating considerations
Individual differences Quantity-quality relation Inter-domain contrasts Impact of extraneous factors
– Negative influences
![Page 49: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/49.jpg)
Complicating considerations
Individual differences Quantity-quality relation Inter-domain contrasts Impact of extraneous factors
– Negative influences: e.g., war
![Page 50: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/50.jpg)
Complicating considerations
Individual differences Quantity-quality relation Inter-domain contrasts Impact of extraneous factors
– Negative influences– Positive influences
![Page 51: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/51.jpg)
Complicating considerations
Individual differences Quantity-quality relation Inter-domain contrasts Impact of extraneous factors
– Negative influences – Positive influences: e.g.,
• disciplinary networks
![Page 52: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/52.jpg)
Complicating considerations
Individual differences Quantity-quality relation Inter-domain contrasts Impact of extraneous factors
– Negative influences – Positive influences: e.g.,
• disciplinary networks• cross-fertilization
![Page 53: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/53.jpg)
Hence, the creative productivity within any given career will show major departures from expectation, some positive and some negative
![Page 54: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/54.jpg)
Three Main Conclusions
Age decrement a highly predictable phenomenon at the aggregate level
Age decrement far more unpredictable at the individual level
Age decrement probably less due to aging per se than to other factors both intrinsic and extrinsic to the creative process
![Page 55: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/55.jpg)
Hence, the possibility of late-life creative productivity increments;
e.g., Michel-Eugène Chevreul
(1786-1889)
![Page 56: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/56.jpg)
References
Simonton, D. K. (1984). Creative productivity and age: A mathematical model based on a two-step cognitive process. Developmental Review, 4, 77-111.
Simonton, D. K. (1989). Age and creative productivity: Nonlinear estimation of an information-processing model. International Journal of Aging and Human Development, 29, 23-37.
![Page 57: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/57.jpg)
References
Simonton, D. K. (1991). Career landmarks in science: Individual differences and interdisciplinary contrasts. Developmental Psychology, 27, 119-130.
Simonton, D. K. (1997). Creative productivity: A predictive and explanatory model of career trajectories and landmarks. Psychological Review, 104, 66-89.
Simonton, D. K. (2004). Creativity in science: Chance, logic, genius, and zeitgeist. Cambridge, England: Cambridge University Press.
![Page 58: Mx agcrprod](https://reader036.vdocuments.mx/reader036/viewer/2022062417/54c01e694a79594e638b457e/html5/thumbnails/58.jpg)