EnB presentatie Fischbacher

Information about EnB presentatie Fischbacher

Published on August 30, 2007

Author: BAWare

Source: authorstream.com

Content

Altruistic Punishment and Human Cooperation:  Altruistic Punishment and Human Cooperation Urs Fischbacher University of Zurich NWO, Utrecht 2004 Fischbacher, Gächter and Fehr, Are People Conditionally Cooperative? Evidence from a Public Goods Experiment, Economics Letters 2001. Fehr and Gächter, Altruistic Punishment in Humans, Nature 2002. Fehr and Fischbacher, Third Party Punishment and Social Norms, Evolution and Human Behavior 2004. Fehr and Fischbacher, The Nature of Human Altruism, Nature 2003. De Quervain, Fischbacher, Treyer, Schellhammer, Schnyder, Buck, and Fehr, The Neural Basis of Altruistic Punishment, Science 2004. Overview:  Overview Human cooperation and strong reciprocity Experimental evidence for strong reciprocity Proximate models of strong reciprocity Altruistic punishment activates reward related areas in the brain Ultimate models of strong reciprocity Humans’ Large-Scale Cooperation:  Humans’ Large-Scale Cooperation Humans societies are a huge anomaly in the animal world. They are based on a detailed division of labor and cooperation of genetically unrelated individuals in large groups. In most animal species there is little division of labor and cooperation is limited to small groups. Why do Humans cooperate?:  Why do Humans cooperate? Strategic cooperation (cooperation to induce cooperation by the other players) in the form of Reciprocal altruism, i.e. self-interested exchanges in repeated interactions, at a scale and in domains of behavior that is unprecedented in the animal world. Reputation-based cooperation is also a powerful force among humans and differs in scale and in kind from what has so far been observed in animals. However, human altruism even goes beyond reciprocal altruism and reputation-based cooperation, taking the form of strong reciprocity. Strong Reciprocity:  Strong Reciprocity Is a combination of altruistic rewarding (strong positive reciprocity) and altruistic punishment (strong negative reciprocity). Altruistic rewarding: A readiness to incur costs to reward others for cooperative, norm-abiding behaviors in the absence of any individual economic benefit for the rewarding individual. Altruistic punishment: A readiness to incur costs to punish others for norm violations in the absence of any individual economic benefits for the punishing individual. Public-Goods Experiment:  Public-Goods Experiment N players get an endowment. Decide simultaneously how many point of they contribute to the public goods. The contributions are summed up, multiplied with a factor F (e.g. 2) and distributed equally between all players. If Fandgt;1, it is efficient to contribute (cooperate). If F/Nandlt;1, it is a dominant strategy not to contribute (defect). Structure mimics the logic of many important real world examples. Whenever individual actions have positive or negative effects on other individuals a similar situation arises: Pollution problems, over-fishing the seas, cooperative production and food-sharing in small-scale societies, cooperative hunting and warfare, etc. Altruistic Rewarding:  Altruistic Rewarding (Fischbacher et al. 2001, see also FKR 93 or BDM 95) Standard public goods situation (endowment =20, N = 4, F=1.6); played only once Subjects can make a conditional contribution to the project, i.e. they fill out a contribution table in which they can condition their contribution on every possible contribution of the others Predictions:  Predictions Selfish subjects (e.g. subjects who cooperate for strategic reasons only) always put in zero into the schedule. Strongly reciprocal subjects’ contribution increases in the average contribution of the other group members. The other subjects’ contribution is a cooperative act which deserves altruistic rewarding. Average schedulesFischbacher, Gächter, Fehr 2001:  0 2 4 6 8 10 12 14 16 18 20 0 2 4 6 8 10 12 14 16 18 20 Average contribution level of other group members Own contribution Hump-shaped 14% Selfish 30% Strong reciprocators 50% Mean (N=44) Average schedules Fischbacher, Gächter, Fehr 2001 Altruistic Punishment (Fehr & Gächter, American Economic Review 2000, Nature 2002):  Altruistic Punishment (Fehr andamp; Gächter, American Economic Review 2000, Nature 2002) Public goods game as above. Six periods to allow for learning and to study the stability of cooperation. At the end of each period group members are informed about individual contributions of other group members without revealing their identities. No repeated interaction with the same subjects. In each period each subject faces new group members. Nobody knows the previous actions of the other group members. Altruistic Punishment: Treatments:  Altruistic Punishment: Treatments Control treatment: exactly as described above. Punishment treatment: adds the opportunity to punish other group members after being informed about their investments. Two Stages in each period The first stage is identical to the control treatment. At the second stage each group member can allocate punishment points to the other members. The first stage payoff of the punished individuals is reduced. Punishing is costly for the punisher. Each € 'invested' into punishment reduces the payoff of the sanctioned player by 3€. Predictions with selfish individuals:  Predictions with selfish individuals Since punishment is costly for the punisher and yields not material benefits no selfish subject will ever punish. If nobody punishes in the punishment condition then the cooperation behavior in the punishment condition is predicted to be identical to the behavior in the control condition. In both treatments cooperation should be zero. Cooperation without and with punishmentSource: Fehr&Gächter Nature 2002:  0 2 4 6 8 10 12 14 16 18 20 1 2 3 4 5 6 7 8 9 10 11 12 Period Mean contribution without punishment Cooperation without and with punishment Source: Fehrandamp;Gächter Nature 2002 Cooperation without and with punishmentSource: Fehr&Gächter Nature 2002:  0 2 4 6 8 10 12 14 16 18 20 1 2 3 4 5 6 7 8 9 10 11 12 Period Mean contribution with punishment without punishment Cooperation without and with punishment Source: Fehrandamp;Gächter Nature 2002 Cooperation with and without punishment Source: Fehr&Gächter Nature 2002:  Cooperation with and without punishment Source: Fehrandamp;Gächter Nature 2002 Punishment:  Punishment Is Punishment an altruistic act?:  Is Punishment an altruistic act? The presence of punishers establishes a credible threat that deters non-cooperation - all group members benefit from this threat. Punished subjects contribute more in the next periods - future interaction partners of the punished subjects benefit from the punishment. Punishing subjects bear costs. Strong reciprocity is documented in dozen of studies:  Strong reciprocity is documented in dozen of studies It has been documented in a wide variety of situations: It applies among strangers. Virtually all experiments implement anonymous interactions among subjects. Confirmed under experimenter-subject anonymity (Berg et al. 1995, Bolton and Zwick 1995, Abbink et al. 1997, etc.) Confirmed under rather high stake levels (Cameron 1999, Fehr, Tougareva andamp; Fischbacher 2002, three months' income) Confirmed under one-shot repetitions (Roth et al. 1991, Fehr et. al 1998, Charness 1996, etc.) Strong variation across different small-scale societies (Henrich, Boyd, Bowles, Camerer, Gintis, Fehr andamp; McElreath 2001) Proximate Motives behind Strong Reciprocity:  Proximate Motives behind Strong Reciprocity Inequity aversion Fehr andamp; Schmidt 1999, Bolton andamp; Ockenfels 2000. Ui = pi – ai | pi – pj | Intention based reciprocity Rabin 1993, Levine 1998, Dufwenberg andamp; Kirchsteiger 2004, Falk andamp; Fischbacher forthcoming. Ui = pi + ri kindnessj-andgt;i pj All theories assume a fairness motive in addition to self interest. Neural Basis of Altruistic punishment De Quervain, Fischbacher, ....., and Fehr, Science 2004:  Neural Basis of Altruistic punishment De Quervain, Fischbacher, ....., and Fehr, Science 2004 There is well documented evidence for reward related areas in the brain (Nucleus Accumbens, Nucleus Caudate). These areas are activated when subjects get reward in the form of Money Beautiful faces Cocain Fairness theories assume that people derive utility from altruistic rewarding and from altruistic punishment. Are reward related areas in the brain also activated when subjects have the opportunity to punish? The basic game:  The basic game Two traders, A and B, are matched anonymously. The good possessed by A is four times more worth for trader B. Thus, if A gives the good to B and B pays A a fair share of the gains from trade both traders can benefit. However, trade takes place sequentially, i.e., A first has to give the good to B, then B pays A. Thus, A has to trust B and B can abuse A's trust by not paying. Both are endowed with 10 MUs. A can send his 10 MUs to B. The experimenter quadruples this amount so that B has, in total, 50 MUs. Then B can send back 25 MUs to A. After B has made his payment decision A has the opportunity to punish B. By spending 1 MU on punishment he can reduce B's income by 2 MUs. A can spend up to 20 MUs on punishment. Behavioral Results:  Behavioral Results The vast majority of A sends the 10 MUs. Roughly 50-60% of the B's send back nothing. Roughly 80% of the A's punish those B's who abuse their trust. Average payoff reduction for the B's is 23 MUs. Treatment conditions:  Treatment conditions Punishment is costly for both A and B (Costly, IC). A is hypothesized to experience a desire to punish cheating and he can in fact punish. Punishment is only symbolic, i.e., A and B have no costs of punishing (Symbolic; IS). A is also hypothesized to experience a desire to punish cheating but he cannot punish. Punishment is free for A but costly for B (Free, IF). A is hypothesized to experience a desire to punish cheating and he can in fact punish - even without a cost. We scanned the brain of player A (with PET) in the sequential trading game when A's trust was abused and A decided whether (and how much) to punish B. Hypothesis:  Hypothesis The possibility for punishing unfair behavior activates reward-related neural circuits. (Nucleus Accumbens, Nucleus Caudate). IF - IS is hypothesized to activate reward related brain regions. IC - IS is also hypothesized to activate reward related brain regions IF-IS and IC-IS do activate the caudate nucleus:  IF-IS and IC-IS do activate the caudate nucleus Individuals with higher caudate activation punish more I:  Individuals with higher caudate activation punish more I Is the activation caused by the punishment act? Individuals with higher caudate activation punish more II :  Individuals with higher caudate activation punish more II Those with high caudate activation in IF treatment punished more in the IC treatment. Caudate activation has to do with expected satisfaction of punishment. Overview:  Overview Human cooperation and strong reciprocity Experimental evidence for strong reciprocity Proximate models of strong reciprocity Altruistic punishment activates reward related areas in the brain Ultimate models of strong reciprocity Prevailing Evolutionary Theories of Human Cooperation :  Prevailing Evolutionary Theories of Human Cooperation Kin Selection (Hamilton 1964) - Individuals are genetically related Reciprocal Altruism (Trivers 1971, Axelrod and Hamilton 1981) - Individuals are engaged in repeated interactions. Helping today yields benefits from the other individual in the future. Indirect Reciprocity (Alexander 1987, Nowak and Sigmund 1998) - Helping creates a good reputation in the group. Individuals with a good reputation are more likely to receive help from others in the future. Signaling (Zahavi and Zahavi 1997) - Cooperative acts signal personal qualities that are not directly observable like, e.g., good genes. The signals generate some benefits in the future. Problem of the Theories in Explaining Large-Scale Cooperation:  Problem of the Theories in Explaining Large-Scale Cooperation Kin selection: Cooperation limited to close kin. Subjects in experiments are unrelated strangers. Reciprocal altruism, indirect reciprocity: Cooperation limited to situation in which reputation can be formed, cooperation in experiments also in one-shot situations. Signaling theory: In the absence of selection between groups it is hard to understand why the signal is pro-social. Moreover, all these theories apply, in principal, equally well to many animal species. They do not answer the question, why humans are such an outlier. Maladaption:  Maladaption Theories above can rationalize strong reciprocity only as a maladaptive trait. i.e., the proximate mechanisms driving human behavior are not yet fine-tuned to interactions among unrelated people in non-repeated interactions where reputational gains are small or absent. Problem of the maladaption hypothesis: Humans are capable to distinguish between situations in which reputation can be gained and situation in which this is impossible. Ultimatum game(Güth et al. 1982):  Ultimatum game (Güth et al. 1982) A proposer and a responder are matched anonymously. The proposer receives 10 money units and must make one proposal how to allocate the money between the two players. If the responder accepts, the proposal is implemented. If he rejects, both get nothing. Ultimatum game with reputation:  Ultimatum game with reputation Treatment condition without reputation: Normal ultimatum game. Repeated with different players. Treatment condition with reputation: Proposers get to know which offers were rejected in the past by the responder they are matched with. Repeated with different players. Maladaption prediction: Subject cannot distinguish between situations in which they can build up reputation and situation in which they cannot. Therefore: Whether responders can build up reputation for being tough or not, they have the same threshold for accepting. Average Rejection Threshold in Ultimatum Game with and without Reputation Formation(Source: Fehr and Fischbacher, NATURE 2003):  Average Rejection Threshold in Ultimatum Game with and without Reputation Formation (Source: Fehr and Fischbacher, NATURE 2003) Rejection Threshold in Ultimatum Game with and without Reputation Formation(Source: Fehr and Fischbacher, NATURE 2003):  Rejection Threshold in Ultimatum Game with and without Reputation Formation (Source: Fehr and Fischbacher, NATURE 2003) 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Threshold without reputation Threshold with reputation Rejection Threshold in Ultimatum Game with and without Reputation Formation(Source: Fehr and Fischbacher, NATURE 2003):  Rejection Threshold in Ultimatum Game with and without Reputation Formation (Source: Fehr and Fischbacher, NATURE 2003) 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Threshold without reputation Threshold with reputation The Evolution of Altruistic PunishmentBoyd, Bowles, Gintis and Richersen, PNAS 2003:  The Evolution of Altruistic Punishment Boyd, Bowles, Gintis and Richersen, PNAS 2003 Types of behavior Contributors: incur cost c to produce total benefit b, which is shared equally among n group members. Defectors: incur no costs and produce no benefits. Altruistic Punishers: contribute and punish all those who defect at cost k for themselves and cost p for each defector. If there are no punishers, individual selection favors defectors over contributors. If punishers are frequent, defectors do worse than altruistic punishers and contributors. However, contributors do always better than altruistic punishers. The Evolution of Altruistic Punishment IIBoyd, Bowles, Gintis and Richersen, PNAS 2003:  The Evolution of Altruistic Punishment II Boyd, Bowles, Gintis and Richersen, PNAS 2003 Evolutionary dynamics Individual selection: Individuals imitate more successful individuals within the group. Migration between groups. Group selection mechanism: With some probability unsuccessful groups are extinct and replaced by successful groups. Simulation Results Fehr/Fischbacher, Nature 2003; based on Boyd et al. PNAS 2003:  0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 4 8 16 32 64 128 256 Group size Average cooperation rate no punishment possible Simulation Results Fehr/Fischbacher, Nature 2003; based on Boyd et al. PNAS 2003 Simulation Results Fehr/Fischbacher, Nature 2003; based on Boyd et al. PNAS 2003:  0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 4 8 16 32 64 128 256 Group size Average cooperation rate punishment of defectors possible no punishment possible Simulation Results Fehr/Fischbacher, Nature 2003; based on Boyd et al. PNAS 2003 Why Does Selection not Remove Altruistic Punishers?:  Why Does Selection not Remove Altruistic Punishers? If punishers are frequent and defectors are rare, punishers rarely incur the cost of punishment. Thus, in the absence of mutant defectors punishers would do equally well as pure contributors. In the presence of mutant defectors punishers have a small disadvantage relative to pure contributors. Selection among groups can outweigh this disadvantage of altruistic punishers. Remark: Group selection without punishment does not work: Without punishment cooperators have a fitness disadvantage independent of their frequency. Simulation Results Fehr/Fischbacher, Nature 2003; based on Boyd et al. PNAS 2003:  Simulation Results Fehr/Fischbacher, Nature 2003; based on Boyd et al. PNAS 2003 Why does Migration not Undermine Group Selection?:  Why does Migration not Undermine Group Selection? Because it is based on a cultural process of payoff-biased imitation. Those who have a high payoff are imitated. Traditionally, in genetic models of group selection migration and within-group selection remove between-group differences in the share of defectors. Thus, group selection cannot become operative. Payoff-biased imitation maintains group differences. In groups with a low share of altruistic punishers defectors do best and they are imitated. In groups with a high share of punishers, contributors do best and they are imitated and defectors do worst. Summary:  Summary Human cooperation represents a spectacular outlier in the animal world. This is probably due to human forms of altruism that are unique in kind and in scope. Reciprocal altruism and reputation-seeking are powerful forces of cooperation in dyadic interactions. However, humans exhibit even strong reciprocity, a combination of altruistic rewarding and altruistic punishment that is associated with net costs for the altruist. Altruistic punishment is key for understanding cooperation in multi-lateral interactions. Without altruistic punishment cooperation unravels; if opportunities for altruistic punishment exist cooperation flourishes. Humans seem to experience altruistic punishment as psychologically rewarding. Caudate nucleus is a key component in the neural circuits involved in altruistic punishment. Reciprocal altruism and reputation-seeking are powerful forces of cooperation in dyadic interactions but they have difficulties in explaining the evolution of cooperation in N-person public goods situations. The end:  The end Conditional cooperation design:  Conditional cooperation design (Fischbacher et al. 2001, see also FKR 93 or BDM 95) Standard public goods situation (endowment =20, N = 4, F=1.6); played only once Subjects have to make two decisions: An unconditional contribution to the project A conditional contribution to the project (conditional on every possible contribution of the others – called „contribution table') For 3 subjects, their unconditional contribution is relevant. For a randomly selected group member his/her contribution schedule is relevant for the decision. Testing Evolutionary Models:  Testing Evolutionary Models Environment Game(s) Types of behavior Evolutionary Dynamics Are the types complete? Are there no type who can invade the population? Does the type distribution correspond the distribution which is actually observed? This question can be addressed with experiments. Is the environment representative? Does the game correspond the the interaction how it actually took place in the relevant time period? Simulation Results Fehr/Fischbacher, Nature 2003; based on Boyd et al. PNAS 2003:  Simulation Results Fehr/Fischbacher, Nature 2003; based on Boyd et al. PNAS 2003 Typical experimental outcome Isaac, Walker, Thomas (1984):  Typical experimental outcome Isaac, Walker, Thomas (1984) There is cooperation. Cooperation declines over time. 10H:N=10, F=7.5 4H: N=4, F=3 10L: N=10, F=3 4L: N=4, F=1.2;

Related presentations


Other presentations created by BAWare

Integration into the SDLC
30. 08. 2007
0 views

Integration into the SDLC

hot topic
28. 09. 2007
0 views

hot topic

hispanics
01. 10. 2007
0 views

hispanics

zhang
10. 10. 2007
0 views

zhang

schwa
30. 08. 2007
0 views

schwa

aocc
30. 08. 2007
0 views

aocc

Pedersen
30. 08. 2007
0 views

Pedersen

Mining Sciences
30. 08. 2007
0 views

Mining Sciences

Intelligence Gathering mallorca
30. 08. 2007
0 views

Intelligence Gathering mallorca

ppt00021
30. 08. 2007
0 views

ppt00021

hoe wat over adsl
30. 11. 2007
0 views

hoe wat over adsl

The Healthy Potato
04. 12. 2007
0 views

The Healthy Potato

KINDS OF NOUNS
05. 11. 2007
0 views

KINDS OF NOUNS

CUPA 2007 Adv HW part 3
07. 11. 2007
0 views

CUPA 2007 Adv HW part 3

p Javier Carrillo
14. 11. 2007
0 views

p Javier Carrillo

High Intensity Interval Training
13. 12. 2007
0 views

High Intensity Interval Training

measurement
17. 12. 2007
0 views

measurement

OWASP AppSecEU2006 AJAX Security
30. 08. 2007
0 views

OWASP AppSecEU2006 AJAX Security

Feb05Sepracor
29. 11. 2007
0 views

Feb05Sepracor

aula17
28. 12. 2007
0 views

aula17

lab 04
11. 12. 2007
0 views

lab 04

cattle2000
31. 12. 2007
0 views

cattle2000

Mechanized Logging
02. 01. 2008
0 views

Mechanized Logging

Lightning Safety
03. 01. 2008
0 views

Lightning Safety

water problems
21. 11. 2007
0 views

water problems

mideastmaps
07. 01. 2008
0 views

mideastmaps

schulze
12. 10. 2007
0 views

schulze

Sept 17 03B
19. 11. 2007
0 views

Sept 17 03B

Empowerment2
29. 10. 2007
0 views

Empowerment2

LIU MIT 2006
28. 11. 2007
0 views

LIU MIT 2006

USFS Tourism
22. 11. 2007
0 views

USFS Tourism

omni partner guide pps
02. 10. 2007
0 views

omni partner guide pps

convergence
28. 12. 2007
0 views

convergence

sal mauro 061128
28. 02. 2008
0 views

sal mauro 061128

lec05
29. 02. 2008
0 views

lec05

nypss nsta nov 2003
26. 06. 2007
0 views

nypss nsta nov 2003

Movies MC 061129 3
26. 06. 2007
0 views

Movies MC 061129 3

MOUG 08 2002
26. 06. 2007
0 views

MOUG 08 2002

mold
26. 06. 2007
0 views

mold

moilanen movies
26. 06. 2007
0 views

moilanen movies

MMC Bonato
26. 06. 2007
0 views

MMC Bonato

mm class 8
26. 06. 2007
0 views

mm class 8

Oceans 2005
26. 06. 2007
0 views

Oceans 2005

C3A6
04. 01. 2008
0 views

C3A6

Session8Massimiliano Claps
21. 03. 2008
0 views

Session8Massimiliano Claps

paper Columbia pipelines
30. 08. 2007
0 views

paper Columbia pipelines

CDW Ches99 Talk
05. 01. 2008
0 views

CDW Ches99 Talk

Marketing Mix IPG Presentation
26. 03. 2008
0 views

Marketing Mix IPG Presentation

Moab Marketing
27. 03. 2008
0 views

Moab Marketing

0Kim
30. 08. 2007
0 views

0Kim

Coglx to cultlx
22. 11. 2007
0 views

Coglx to cultlx

12 Igra 4pm
06. 12. 2007
0 views

12 Igra 4pm

Rao
28. 03. 2008
0 views

Rao

Goorevich Richard
30. 03. 2008
0 views

Goorevich Richard

06MYMRes2
09. 04. 2008
0 views

06MYMRes2

quickreview
10. 04. 2008
0 views

quickreview

MontanaDDpresentatio n060105a
13. 04. 2008
0 views

MontanaDDpresentatio n060105a

The Happy Monkey
29. 11. 2007
0 views

The Happy Monkey

cnea 376
20. 11. 2007
0 views

cnea 376

e know GV Presentation
17. 04. 2008
0 views

e know GV Presentation

SustainabilityCaseSt udies
22. 04. 2008
0 views

SustainabilityCaseSt udies

mark
30. 08. 2007
0 views

mark

Dialectal Differentiation
24. 11. 2007
0 views

Dialectal Differentiation

Chapter01
30. 08. 2007
0 views

Chapter01

n0102 SPIE1
26. 06. 2007
0 views

n0102 SPIE1

tues RMI cloonan
07. 12. 2007
0 views

tues RMI cloonan

Modi
26. 06. 2007
0 views

Modi

mne tools scripts kskassam
26. 06. 2007
0 views

mne tools scripts kskassam

hausmesse vortrag meyer
16. 11. 2007
0 views

hausmesse vortrag meyer

sjw
21. 12. 2007
0 views

sjw

stew cartons
17. 06. 2007
0 views

stew cartons

stellmach tim
17. 06. 2007
0 views

stellmach tim

Twelfth Night 2
17. 06. 2007
0 views

Twelfth Night 2

tuebingen seminar nov 04
17. 06. 2007
0 views

tuebingen seminar nov 04

TNG Presentation1
17. 06. 2007
0 views

TNG Presentation1

THE SCIENCE OF LOVE
17. 06. 2007
0 views

THE SCIENCE OF LOVE

t06B Functions Examples
17. 06. 2007
0 views

t06B Functions Examples

Sunny
17. 06. 2007
0 views

Sunny

28 1330 HARP rohacs hideg
18. 03. 2008
0 views

28 1330 HARP rohacs hideg

Water way Awareness
17. 06. 2007
0 views

Water way Awareness

Watergate Political Cartoons
17. 06. 2007
0 views

Watergate Political Cartoons

Valentine s PPT
17. 06. 2007
0 views

Valentine s PPT

USB FunctionDrv
17. 06. 2007
0 views

USB FunctionDrv

urban legends
17. 06. 2007
0 views

urban legends

unti 17Le 1 Funny stories
17. 06. 2007
0 views

unti 17Le 1 Funny stories

Understanding Political Cartoons
17. 06. 2007
0 views

Understanding Political Cartoons

Week2 Augustineandhisera
17. 06. 2007
0 views

Week2 Augustineandhisera

Tee
09. 10. 2007
0 views

Tee

seshun
13. 11. 2007
0 views

seshun

Locke 1 07
30. 08. 2007
0 views

Locke 1 07

ames tornado
05. 10. 2007
0 views

ames tornado

TEAM 9
08. 11. 2007
0 views

TEAM 9

Ferragina
23. 11. 2007
0 views

Ferragina

robo wk 4 controls
07. 01. 2008
0 views

robo wk 4 controls

ScottStroup
02. 11. 2007
0 views

ScottStroup

dyer w ref
04. 03. 2008
0 views

dyer w ref

act31sld
30. 08. 2007
0 views

act31sld

WA Final
17. 06. 2007
0 views

WA Final

What to do in Harrisonburg
17. 06. 2007
0 views

What to do in Harrisonburg