Asam100bbXinyu ShangReading journal week1In the article Im.docx

Asam100bb
Xinyu Shang
Reading journal week1
In the article Immigration and Livelihood, 1840s to 1930s, the
key reason why the Asians moved to the United States was to
look for jobs. The Asians were desperate for jobs and were
ready to work even if they received low salaries. On the other
hand, their employers loved the situation since they made a lot
of profits. The first Asians to enter the United States made it
through the Manila galleon trade. “An act for the governance of
masters and servants” (Chan, 1991 p25). However, other
communities felt as if the Asians brought competition, which
could result in a reduction of job opportunities. Some of these
were the Euro-Americans employees who saw the Asians as
their competitors. Others were the nativists for all levels who
were aggressive to them since they stopped them for restless
reasons to prevent their coming.
Azuma Introduction tells that people who were born in Japan
and later on shifted to America for studies had the right to
express their views without any restrictions. Both the Tateishi
and the Hoashi had not gotten a chance to become leaders in the
Japenese colonist community, and they were not even
recognized in America. “East is West West is East” (Azuma,
2005 p9). However, their routes were not highly valued
compared to their expressions, especially during their times.
These two communities had the capability of offering their
shared predicament comprehensibly in public. Linking with the
article on Mercantilists, Colonialists, and Laborers, the dilemma
of these communities living through the claimed the separation
for the East-West separation and linked binaries. The article
also concentrates on the global history of Japanese immigrants
and the procedure of creating the racial process. Additionally,
the collective impacts of the organizational and figurative

regulators control the experience of a marginal group that was
viewed as a racial project.Chapter one talks about theoretical
groups and how they are confusing. There was considerable
confusion on whether the Japanese who relocated to the United
States were there to colonize the U.S, or they had just come as
immigrants. “Going to America” (Azuma, 2005 p23). The
difficulty categorized the historical course of Japanese
relocation to the United States as a varied nature of the early
Issue community. It is clear that later on, after the Japanese
had shifted to the United States, they implemented their
capitalist economy, which brought more confusion concerning
the issue of immigration and colonization. Therefore, this was
one of the intercontinental histories of Japanese immigration in
the American West, which brought about the contradiction
issue.
On the Takaki talks about how the Chinese moved to one of the
cities in the United States known as California. It happened to
be a movement that had been formed by several people from
various nations. These were inclusive of the Korean, Chinese,
Filipino, and Japanese. “Cheap labor” (Takaki, 1993 p132)
.They were supposed to shift to Hawaii, which was an American
territory. All these came here to look for labor for them to make
a living. They worked in an industry that produced sugar.
Hawaii was very different from other states such as California
in various perspectives, such as ethical wise. Chapter five
speaks on how the Japanese finally settled in the United States
in California to be specific. It also indicates the level of racism
that the Japanese experienced while in the United States. A
young man whose origin was Hawaai stated that he experienced
how badly the Japanese were treated in California. “But I didn’t
realize the situation until I had a real experience “(Takaki, 1993
p180). It was after he had gone to get a shave, and upon the
barber realizing his nationality, he refused to attend to him and
instead chased him out of his shape. The Japanese were also
mistreated as laborers by receiving peanuts and having poor
working conditions.

BIBLIOGRAPHY 1
Prediction, persuasion, and the jurisprudence of behaviourism
Contents
1. I Introduction
2. II Stacking the deck: ‘predicting’ the contemporaneous
3. III Problematic characteristics of the ECtHR textual
‘predictive’ model
4. IV Conclusion
5. Footnotes
Full Text
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There is a growing literature critiquing the unreflective
application of big data, predictive analytics, artificial
intelligence, and machine-learning techniques to social
problems. Such methods may reflect biases rather than reasoned
decision making. They also may leave those affected by
automated sorting and categorizing unable to understand the
basis of the decisions affecting them. Despite these problems,
machine-learning experts are feeding judicial opinions to
algorithms to predict how future cases will be decided. We call
the use of such predictive analytics in judicial contexts a
jurisprudence of behaviourism as it rests on a fundamentally
Skinnerian model of cognition as a black-boxed transformation
of inputs into outputs. In this model, persuasion is passé; what
matters is prediction. After describing and critiquing a recent
study that has advanced this jurisprudence of behaviourism, we
question the value of such research. Widespread deployment of
prediction models not based on the meaning of important
precedents and facts may endanger the core rule-of-law values.
artificial intelligence; cyber law; machine learning;

jurisprudence; predictive analysis
I Introduction
A growing chorus of critics are challenging the use of opaque
(or merely complex) predictive analytics programs to monitor,
influence, and assess individuals’ behaviour. The rise of a
‘black box society’ portends profound threats to individual
autonomy; when critical data and algorithms cannot be a matter
of public understanding or debate, both consumers and citizens
are unable to comprehend how they are being sorted,
categorized, and influenced.[ 2]
A predictable counter-argument has arisen, discounting the
comparative competence of human decision makers. Defending
opaque sentencing algorithms, for instance, Christine
Remington (a Wisconsin assistant attorney general) has stated:
‘We don’t know what’s going on in a judge’s head; it’s a black
box, too.’[ 3] Of course, a judge must (upon issuing an
important decision) explain why the decision was made; so too
are agencies covered by the Administrative Procedure Act
obliged to offer a ‘concise statement of basis and purpose’ for
rule making.[ 4] But there is a long tradition of realist
commentators dismissing the legal justifications adopted by
judges as unconvincing fig leaves for the ‘real’ (non-legal)
bases of their decisions.
In the first half of the twentieth century, the realist disdain for
stated rationales for decisions led in at least two directions:
toward more rigorous and open discussions of policy
considerations motivating judgments and toward frank
recognition of judges as political actors, reflecting certain
ideologies, values, and interests. In the twenty-first century, a
new response is beginning to emerge: a deployment of natural
language processing and machine-learning (ML) techniques to
predict whether judges will hear a case and, if so, how they will
decide it. ML experts are busily feeding algorithms with the
opinions of the Supreme Court of the United States, the
European Court of Human Rights, and other judicial bodies as
well as with metadata on justices’ ideological commitments,

past voting record, and myriad other variables. By processing
data related to cases, and the text of opinions, these systems
purport to predict how judges will decide cases, how individual
judges will vote, and how to optimize submissions and
arguments before them.
This form of prediction is analogous to forecasters using big
data (rather than understanding underlying atmospheric
dynamics) to predict the movement of storms. An algorithmic
analysis of a database of, say, 10,000 past cumulonimbi
sweeping over Lake Ontario may prove to be a better predictor
of the next cumulonimbus’s track than a trained meteorologist
without access to such a data trove. From the perspective of
many predictive analytics approaches, judges are just like any
other feature of the natural world – an entity that transforms
certain inputs (such as briefs and advocacy documents) into
outputs (decisions for or against a litigant). Just as forecasters
predict whether a cloud will veer southwest or southeast, the
user of a ML system might use machine-readable case
characteristics to predict whether a rainmaker will prevail in the
courtroom.
We call the use of algorithmic predictive analytics in judicial
contexts an emerging jurisprudence of behaviourism, since it
rests on a fundamentally Skinnerian model of mental processes
as a black-boxed transformation of inputs into outputs.[ 5] In
this model, persuasion is passé; what matters is prediction.[ 6]
After describing and critiquing a recent study typical of this
jurisprudence of behaviourism, we question the value of the
research program it is advancing. Billed as a method of
enhancing the legitimacy and efficiency of the legal system,
such modelling is all too likely to become one more tool
deployed by richer litigants to gain advantages over poorer
ones.[ 7] Moreover, it should raise suspicions if it is used as a
triage tool to determine the priority of cases. Such predictive
analytics are only as good as the training data on which they
depend, and there is good reason to doubt such data could ever
generate in social analysis the types of ground truths

characteristic of scientific methods applied to the natural world.
While fundamental physical laws rarely if ever change, human
behaviour can change dramatically in a short period of time.
Therefore, one should always be cautious when applying
automated methods in the human context, where factors as basic
as free will and political change make the behaviour of both
decision makers, and those they impact, impossible to predict
with certainty.[ 8]
Nor are predictive analytics immune from bias. Just as judges
bring biases into the courtroom, algorithm developers are prone
to incorporate their own prejudices and priors into their
machinery.[ 9] In addition, biases are no easier to address in
software than in decisions justified by natural language. Such
judicial opinions (or even oral statements) are generally much
less opaque than ML algorithms. Unlike many proprietary or
hopelessly opaque computational processes proposed to replace
them, judges and clerks can be questioned and rebuked for
discriminatory behaviour.[ 10] There is a growing literature
critiquing the unreflective application of ML techniques to
social problems.[ 11] Predictive analytics may reflect biases
rather than reasoned decision making.[ 12] They may also leave
those affected by automated sorting and categorizing unable to
understand the basis of the decisions affecting them, especially
when the output from the models in anyway affects one’s life,
liberty, or property rights and when litigants are not given the
basis of the model’s predictions.[ 13]
This article questions the social utility of prediction models as
applied to the judicial system, arguing that their deployment
may endanger core rule-of-law values. In full bloom, predictive
analytics would not simply be a camera trained on the judicial
system, reporting on it, but it would also be an engine of
influence, shaping it. Attorneys may decide whether to pursue
cases based on such systems; courts swamped by appeals or
applications may be tempted to use ML models to triage or
prioritize cases. In work published to widespread acclaim in
2016, Nikolaos Aletras, Dimitrios Tsarapatsanis, Daniel

Preoţiuc-Pietro, and Vasileios Lampos made bold claims about
the place of natural language processing (NLP) in the legal
system in their article Predicting Judicial Decisions of the
European Court of Human Rights: A Natural Language
Processing Perspective.[ 14] They claim that ‘advances in
Natural Language Processing (NLP) and Machine Learning
(ML) provide us with the tools to automatically analyse legal
materials, so as to build successful predictive models of judicial
outcomes.’[ 15] Presumably, they are referring to their own
work as part of these advances. However, close analysis of their
‘systematic study on predicting the outcome of cases tried by
the European Court of Human Rights based solely on textual
content’ reveals that their soi-disant ‘success’ merits closer
scrutiny on both positive and normative grounds.
The first question to be asked about a study like Predicting
Judicial Decisions is: what are its uses and purposes? Aletras
and colleagues suggest at least three uses. First, they present
their work as a first step toward the development of ML and
NLP software that can predict how judges and other authorities
will decide legal disputes. Second, Aletras has clearly stated to
media that artificial intelligence ‘could also be a valuable tool
for highlighting which cases are most likely to be violations of
the European Convention of Human Rights’ – in other words,
that it could help courts triage which cases they should
hear.[ 16] Third, they purport to intervene in a classic
jurisprudential debate – whether facts or law matter more in
judicial determinations.[ 17] Each of these aims and claims
should be rigorously interrogated, given shortcomings of the
study that the authors acknowledge. Beyond these
acknowledged problems, there are even more faults in their
approach which cast doubt on whether the research program of
NLP-based prediction of judicial outcomes, even if pursued in a
more realistic manner, has anything significant to contribute to
our understanding of the legal system.
Although Aletras and colleagues have used cutting edge ML and
NLP methods in their study, their approach metaphorically

stacks the deck in favour of their software and algorithms in so
many ways that it is hard to see its relevance to either practising
lawyers or scholars. Nor is it plausible to state that a method
this crude, and disconnected from actual legal meaning and
reasoning, provides empirical data relevant to jurisprudential
debates over legal formalism and realism. As more advanced
thinking on artificial intelligence and intelligence augmentation
has already demonstrated, there is an inevitable interface of
human meaning that is necessary to make sense of social
institutions like law.
II Stacking the deck: ‘predicting’ the contemporaneous
The European Court of Human Rights (ECtHR) hears cases in
which parties allege that their rights under the articles of the
European Convention of Human Rights were violated and not
remedied by their country’s courts.[ 18] The researchers claim
that the textual model has an accuracy of ‘79% on
average.’[ 19] Given sweepingly futuristic headlines generated
by the study (including ‘Could AI [Artificial Intelligence]
Replace Judges and Lawyers?’), a casual reader of reports on
the study might assume that this finding means that, using the
method of the researchers, those who have some aggregation of
data and text about case filings can use that data to predict how
the ECtHR will decide a case, with 79 per cent accuracy.[ 20]
However, that would not be accurate. Instead, the researchers
used the ‘circumstances’ subsection in the cases they claimed to
‘predict,’ which had ‘been formulated by the Court itself.’[ 21]
In other words, they claimed to be ‘predicting’ an event (a
decision) based on materials released simultaneously with the
decision. This is a bit like claiming to ‘predict’ whether a judge
had cereal for breakfast yesterday based on a report of the
nutritional composition of the materials on the judge’s plate at
the exact time she or he consumed the breakfast.[ 22] Readers
can (and should) balk at using the term ‘prediction’ to describe
correlations between past events (like decisions of a court) and
contemporaneously generated, past data (like the circumstances
subsection of a case). Sadly, though, few journalists

breathlessly reporting the study by Aletras and colleagues did
so.
To their credit, though, Aletras and colleagues repeatedly
emphasize how much they have effectively stacked the deck by
using ECtHR-generated documents themselves to help the
ML/NLP software they are using in the study ‘predict’ the
outcomes of the cases associated with those documents. A truly
predictive system would use the filings of the parties, or data
outside the filings, that was in existence before the judgement
itself. Aletras and colleagues grudgingly acknowledge that the
circumstances subsection ‘should not always be understood as a
neutral mirroring of the factual background of the case,’ but
they defend their method by stating that the ‘summaries of facts
found in the “Circumstances” section have to be at least framed
in as neutral and impartial a way as possible.’[ 23] However,
they give readers no clear guide as to when the circumstances
subsection is actually a neutral mirroring of factual background
or how closely it relates to records in existence before a
judgment that would actually be useful to those aspiring to
develop a predictive system.
Instead, their ‘premise is that published judgments can be used
to test the possibility of a text-based analysis for ex ante
predictions of outcomes on the assumption that there is enough
similarity between (at least) certain chunks of the text of
published judgments and applications lodged with the Court
and/or briefs submitted by parties with respect to pending
cases.’[ 24] But they give us few compelling reasons to accept
this assumption since almost any court writing an opinion to
justify a judgment is going to develop a facts section in ways
that reflect its outcome. The authors state that the ECtHR has
‘limited fact finding powers,’ but they give no sense of how
much that mitigates the cherry-picking of facts or statements
about the facts problem. Nor should we be comforted by the fact
that ‘the Court cannot openly acknowledge any kind of bias on
its part.’ Indeed, this suggests a need for the Court to avoid the
types of transparency in published justification that could help

researchers artificially limited to NLP better understand it.[ 25]
The authors also state that in the ‘vast majority of cases,’ the
‘parties do not seem to dispute the facts themselves, as
contained in the “Circumstances” subsection, but only their
legal significance.’ However, the critical issues here are, first,
the facts themselves and, second, how the parties characterized
the facts before the circumstances section was written. Again,
the fundamental problem of mischaracterization – of
‘prediction’ instead of mere correlation or relationship – crops
up to undermine the value of the study.
Even in its most academic mode – as an ostensibly empirical
analysis of the prevalence of legal realism – the study by
Aletras and colleagues stacks the deck in its favour in important
ways. Indeed, it might be seen as assuming at the outset a
version of the very hypothesis it ostensibly supports. This
hypothesis is that something other than legal reasoning itself
drives judicial decisions. Of course, that is true in a trivial
sense – there is no case if there are no facts – and perhaps the
authors intend to make that trivial point.[ 26] However, their
language suggests a larger aim, designed to meld NLP and
jurisprudence. Given the critical role of meaning in the latter
discipline, and their NLP methods’ indifference to it, one might
expect an unhappy coupling here. And that is indeed what we
find.
In the study by Aletras and colleagues, the corpus used for the
predictive algorithm was a body of ECtHR’s ‘published
judgments.’ Within these judgments, a summary of the factual
background of the case was summarized (by the Court) in the
circumstances section of the judgments, but the pleadings
themselves were not included as inputs.[ 27] The law section,
which ‘considers the merits of the case, through the use of legal
argument,’ was also input into the model to determine how well
that section alone could ‘predict’ the case outcome.[ 28]
Aletras and colleagues were selective in the corpus they fed to
their algorithms. The only judgments that were included in the
corpus were those that passed both a ‘prejudicial stage’ and a

second review.[ 29] In both stages, applications were denied if
they did not meet ‘admissibility criteria,’ which were largely
procedural in nature.[ 30] To the extent that such procedural
barriers were deemed ‘legal,’ we might immediately have
identified a bias problem in the corpus – that is, the types of
cases where the law entirely determined the outcome (no matter
how compelling the facts may have been) were removed from a
data set that was ostensibly fairly representative of the universe
of cases generally. This is not a small problem either; the
overwhelming majority of applications were deemed
inadmissible or struck out and were not reportable.[ 31]
But let us assume, for now, that the model only aspired to offer
data about the realist/formalist divide in those cases that did
meet the admissibility criteria. There were other biases in the
data set. Only cases that were in English, approximately 33 per
cent of the total ECtHR decisions, were included.[ 32] This is a
strange omission since the NLP approach employed here had no
semantic content – that is, the meaning of the words did not
matter to it. Presumably, this omission arose out of concerns for
making data coding and processing easier. There was also a
subject matter restriction that further limited the scope of the
sample. Only cases addressing issues in Articles 3, 6, and 8 of
the ECHR were included in training and in verifying the model.
And there is yet another limitation: the researchers then threw
cases out randomly (so that the data set contained an equal
number of violation/no violation cases) before using them as
training data.[ 33]
III Problematic characteristics of the ECtHR textual ‘predictive’
model
The algorithm used in the case depended on an atomization of
case language into words grouped together in sets of one-, two-,
three-, and four-word groupings, called n-grams.[ 34] Then,
2,000 of the most frequent n-grams, not taking into
consideration ‘grammar, syntax and word order,’ were placed in
feature matrices for each section of decisions and for the entire
case by using the vectors from each decision.[ 35] Topics,

which are created by ‘clustering together n-grams,’ were also
created.[ 36] Both topics and n-grams were used to ‘to train
Support Vector Machine (SVM) classifiers.’ As the authors
explain, an ‘SVM is a machine learning algorithm that has
shown particularly good results in text classification, especially
using small data sets.’[ 37] Model training data from these
opinions were ‘n-gram features,’ which consist of groups of
words that ‘appear in similar contexts.’[ 38] Matrix
mathematics, which are manipulations on two-dimensional
tables, and vector space models, which are based on a single
column within a table, were programmed to determine clusters
of words that should be similar to one another based on textual
context.[ 39] These clusters of words are called topics. The
model prevented a word group from showing up in more than
one topic. Thirty topics, or sets of similar word groupings, were
also created for entire court opinions. Topics were similarly
created for entire opinions for each article.[ 40] Since the court
opinions all follow a standard format, the opinions could be
easily dissected into different identifiable sections.[ 41] Note
that these sorting methods are legally meaningless. N-grams and
topics are not sorted the way a treatise writer might try to
organize cases or a judge might try to parse divergent lines of
precedent. Rather, they simply serve as potential independent
variables to predict a dependent variable (was there a violation,
or was there not a violation, of the Convention).
Before going further into the technical details of the study, it is
useful to compare it to prior successes of ML in facial or
number recognition. When a facial recognition program
successfully identifies a given picture as an image of a given
person, it does not achieve that machine vision in the way a
human being’s eye and brain would do so. Rather, an initial
training set of images (or perhaps even a single image) of the
person are processed, perhaps on a 1,000-by-1,000-pixel grid.
Each box in the grid can be identified as either skin or not skin,
smooth or not smooth, along hundreds or even thousands of
binaries, many of which would never be noticed by a human

being. Moreover, such parameters can be related to one another;
so, for example, regions hued as ‘lips’ or ‘eyes’ might have a
certain maximum length, width, or ratio to one another (such
that a person’s facial ‘signature’ reliably has eyes that are 1.35
times as long as they are wide). Add up enough of these ratios
for easily recognized features (ears, eyebrows, foreheads, and
so on), and software can quickly find a set of mathematical
parameters unique to a given person – or at least unique enough
that an algorithm can predict that a given picture is, or is not, a
picture of a given person, with a high degree of accuracy. The
technology found early commercial success with banks, which
needed a way to recognize numbers on cheques (given the wide
variety of human handwriting). With enough examples of
written numbers (properly reduced to data via dark or filled
spaces on a grid), and computational power, this recognition can
become nearly perfect.
Before assenting too quickly to the application of such methods
to words in cases (as we see them applied to features of faces),
we should note that there are not professions of ‘face
recognizers’ or ‘number recognizers’ among human beings. So
while Facebook’s face recognition algorithm, or TD Bank’s
cheque sorter, do not obviously challenge our intuitions about
how we recognize faces or numbers, applying ML to legal cases
should be marked as a jarring imperialism of ML methods into
domains associated with a rich history of meaning (and, to use a
classic term from the philosophy of social sciences, Verstehen).
In the realm of face recognizing, ‘whatever works’ as a
pragmatic ethic of effectiveness underwrites some societies’
acceptance of width/length ratios and other methods to assure
algorithmic recognition and classification of individuals.[ 42]
The application of ML approaches devoid of apprehension of
meaning in the legal context is more troubling. For example,
Aletras and colleagues acknowledge that there are cases where
the model predicts the incorrect outcome because of the
similarity in words in cases that have opposite results. In this
case, even if information regarding specific words that triggered

the SVM classifier were output, users might not be able to
easily determine that the case was likely misclassified.[ 43]
Even with confidence interval outputs, this type of problem
does not appear to have an easy solution. This is particularly
troubling for due process if such an algorithm, in error,
incorrectly classified someone’s case because it contained
language similarities to another very different case.[ 44] When
the cases are obviously misclassified in this way, models like
this would likely ‘surreptitiously embed biases, mistakes and
discrimination, and worse yet, even reiterate and reinforce them
on the new cases processed.’[ 45] So, too, might a batch of
training data representing a certain time period when a certain
class of cases were dominant help ensure the dominance of such
cases in the future. For example, the ‘most predictive topic’ for
Article 8 decisions included prominently the words ‘son, body,
result, Russian.’ If the system were used in the future to triage
cases, ceteris paribus, it might prioritize cases involving sons
over daughters or Russians over Poles.[ 46] But if those future
cases do not share the characteristics of the cases in the training
set that led to the ‘predictiveness’ of ‘son’ status or ‘Russian’
status, their prioritization would be a clear legal mistake.
Troublingly, the entire ‘predictive’ project here may be riddled
with spurious correlations. As any student of statistics knows, if
one tests enough data sets against one another, spurious
correlations will emerge. For example, Tyler Vigen has shown a
very tight correlation between the divorce rate in Maine and the
per capita consumption of margarine between 2000 and
2009.[ 47] It is unlikely that one variable there is driving the
other. Nor is it likely that some intervening variable is affecting
both butter consumption and divorce rates in a similar way, to
ensure a similar correlation in the future. Rather, this is just the
type of random association one might expect to emerge once
one has thrown enough computing power at enough data sets.
It is hard not to draw similar conclusions with respect to Aletras
and colleagues’ ‘predictive’ project. Draw enough variations
from the ‘bag of words,’ and some relationships will emerge.

Given that the algorithm only had to predict ‘violation’ or ‘no
violation,’ even a random guessing program would be expected
to have a 50 per cent accuracy rate. A thought experiment easily
deflates the meaning of their trumpeted 79 per cent ‘accuracy.’
Imagine that the authors had continual real time surveillance of
every aspect of the judges’ lives before they wrote their
opinions: the size of the buttons on their shirts and blouses,
calories consumed at breakfast, average speed of commute,
height and weight, and so forth. Given a near infinite number of
parameters of evaluation, it is altogether possible that they
could find that a cluster of data around breakfast type, or button
size, or some similarly irrelevant characteristics, also added an
increment of roughly 29 per cent accuracy to the baseline 50 per
cent accuracy achieved via randomness (or always guessing
violation). Should scholars celebrate the ‘artificial intelligence’
behind such a finding? No. Ideally, they would chuckle at it, as
readers of Vigen’s website find amusement at random
relationships between, say, number of letters in winning words
at the National Spelling Bee and number of people killed by
venomous spiders (which enjoys a 80.57 per cent correlation).
This may seem unfair to Aletras and colleagues since they are
using so much more advanced math than Vigen is. However,
their models do not factor in meaning, which is of paramount
importance in rights determinations. To be sure, words like
‘burial,’ ‘attack,’ and ‘died’ do appear properly predictive, to
some extent, in Article 8 decisions and cause no surprise when
they are predictive of violations.[ 48] But what are we to make
of inclusion of words like ‘result’ in the same list? There is
little to no reasoned explanation in their work as to why such
words should be predictive with respect to the corpus, let alone
future case law.
This is deeply troubling, because it is a foundational principle
of both administrative and evidence law that irrelevant factors
should not factor into a decision. To be sure, there is little
reason the ECtHR would use such a crude model to determine
the outcome of cases before it or even to use it as a decision

aide. However, software applications often are used in ways for
which they were not intended. When they are billed as
predictive models, attorneys and others could likely use the
models for their own triage purposes. This is especially
dangerous when attorneys are generally not very familiar with
statistical analysis and ML. The legal community’s ability to
scrutinize such models, and correctly interpret their results, is
questionable.[ 49] Journalistic hype around studies like this one
shows that public understanding is likely even more
impaired.[ 50]
Aletras and colleagues are aware of many problems with their
approach, and, in the paper, they continually hedge about its
utility. But they still assert:
Overall, we believe that building a text-based predictive system
of judicial decisions can offer lawyers and judges a useful
assisting tool. The system may be used to rapidly identify cases
and extract patterns that correlate with certain outcomes. It can
also be used to develop prior indicators for diagnosing potential
violations of specific Articles in lodged applications and …
Asam100bb
Xinyu Shang
The beginning of the chapter narrates the rapport of the
immigrant Japanese among the Americans and the Japanese-
Americans in the early 1880s. The immigrant Japanese were
mostly low-incomed people with illegal wives who were being
pushed into prostitution by their husbands to make the ends
meet. Most of these people were poor laborers, brothel owners
and relied on unethical means of earning. They were involved in
gambling and addiction which created a narrative of all the
Japanese which affected the lives of the Japanese-Americans.
The last decade of the nineteenth century caused havoc on the
Japanese when the immigration officer declared them as illegal
contractors and was denied entry in America, just like Chinese.

Issei i.e. the first generation Japanese-Americans and the elite
immigrants saw this as a threat to their social image and a cause
for racial discrimination thus they made it very clear how they
are different from the Chinese. Issei leaders stated, How do
Japanese in America and the Chinese in America differ? First,
the Chinese in America represent the lower class of the Chinese
race, and the Japanese in America the upper class of the
Japanese race. Second, the Chinese are so backward and
stubborn that they refuse the American way. The Japanese, on
the other hand, are so progressive and competent as to fit right
into the American way of life….In no way do we, energetic and
brilliant Japanese men, stand below those lowly Chinese
(Azuma,ch2).
The divergence of the Japanese-Americans escalated as they
believed the shabbily clothed laborers do not represent the
Japanese and do not meet the standard American lifestyle. The
bubble of the Issei leaders burst when the San Francisco Board
of Health forcefully tackled the elite and vaccinated them in
their groins during the outbreak of Sinification. They began to
realize they were nonetheless better than the Chinese according
to the Americans. This led to the formation of the Japanese
Deliberative Council of America whose aim was to save the
national stature of the Japanese and increasing the rights of
imperial issues. A significant decrease in meager jobs like
mining and manual workers was observed in the twentieth
century among the Japanese. The Gentlemen’s Agreement was
signed between the American and Japanese governments which
terminated the influx of the dekasegi migrants into America.
This resulted in jeopardizing the economic sources of Issei
contractors who used to hire these laborers.
The political riots up roared in Japan in the early 1900s and the
socialist and the leftist groups took refuge in San Francisco.
The blasphemous leaflets against Emperor Meiji were
distributed in which the Diplomats try to cover up with the
American authorities but it was useless and thus Foreign
Ministers of Japan ordered the prosecution of the socialists

upon their return to Japan.
Meanwhile many reformative measures were being also taken
such as anti-gambling campaigns and educating the rural
masses. This was also being done to shed the narrative of being
associated with the corrupt Chinese. The women were being
tutored by the elite Issei Japanese to be more palatable to the
American taste. They were being subtly brainwashed to stay in
America, adopt their lifestyle and bear their children and be
more presentable to the Americans to be inclusive of the
American culture. Organizations such as the Japanese Young
Women's Christian Association (YWCA) were formed whose
sole purpose was to introduce the Japanese women as the
modern women who wear western attire and behave lady-like.
Another noticeable community of the diasporic Japanese in the
1920s had been molded who were not being accepted by the
Americans and rejected by the Japanese back home. They
suffered a great deal with racial subordination in the white
American regime. In areas like Walnut Groove, the Issei
farmers had started their successful journey by yielding the top-
quality produce, using the labor of Japanese farmers, which the
white farmers had overlooked and gained profits triple folds.
The Alien Land Law made the farmers more vulnerable and
were being exploited by the tenancy contracts by the hands of
white property owners. This made them more socially and
economically dependent on the Americans and thus they shifted
to shared-cropping which had less monetary benefits for the
farmers. The institutionalized racism and abuse made the
farmers give up on farming.
After the war years, the racial discriminatory lines were blurred
to some extent due to the growing population of the Japanese.
The debate to permit interracial interactions began beyond the
economic ties. America's dismissal of racial equality showed the
American hypocrisy and thus left an adverse impact on the
young Japanese.

Prepared at the end of the quarter, this is your chance to reflect
on the course and the work you have done over the past ten
weeks. This should be written in the style of a letter addressed
either to me or to you. The letters should do two things, namely:
reflect on the course and report/ reflect on the team(s) with
whom you worked during the course. The reflections should
discuss the readings and topics you found most meaningful,
struggles and victories that you had, the ways that elements
from the course connect to your life and/or your other courses,
and your thoughts on what you would do if you took another
course like this. The discussion of your team(s) is your chance
to tell me how things worked (or didn’t) with your classmates.
If everything went fine and everyone contributed, from your
perspective, then you can simply say that. If there were issues
with distribution of work, communication, unequal effort, or
other problems, then please include those. This will help me
adjust the grades for individuals on the team assignments.
Regardless, please also reflect on what you (or I) could do to
improve team projects in the future. The letter can be as long or
as short as you want it to be (though make sure to cover the
required elements).
Length: Probably not less than 1.5 pages, but as long as you
want beyond that Style: Letter
Citation: Mention the authors and use quotations marks if you
quote something
Xinyu Shang
ASAM 100 BB

Reading Journal
This reflection is premised on the YouTube video entitled, “A
community Grows
Despite Racism.” This is a 4 minutes 07 seconds video which
showcase the growth of the
Japanese community in American despite the several efforts and
legislations to
discriminate against them and limit their existence in the United
States. The Japanese
went to the US in search of jobs more than 100 years ago
whereby more than 3000
Japanese found their way into the United States. They migrated
to the Haiwai mainland
to work as farmers, plantation workers, fishermen, and railway
workers.
However, despite their hard work, the Japanese remained
unwelcome. For
example, Frank Miyamoto explains what made his father left
Carrington. He says that the
father found workplace harassment unpleasant as he was
discriminated against by the
White workers. The Japanese were threatened both workers and
their families. Besides

the harassment at work, the Americans passed laws that
discriminated against the
Japanese and even the Supreme Court (in 1922) ruled that the
Japanese could not be
naturalized in attempts to limit their growth. For example, the
anti-alien laws in
California were enacted (in 1913) to bar Japanese from owning
land. Congress also
passed the Immigration Act in 1924 which halted the Japanese
migration to the United
States.
Nonetheless, despite all these efforts to restrict the number of
the Japanese, the
community grew as the next generation was born. This
generation were US citizens by
birthrights and adapted to the American way of life as they
attended public schools and
grew up with their non-Japanese American children's
classmates. However,
discrimination of this new generation continued in restaurants,
theater and swimming
pools where they were treated differently as their fellow white
American children

counterparts even in 1940 CRO. This is explained by Frank
Yamasaki who gives an
account of how the new Japanese generation born in America
continued facing
discrimination. He gives an account of how he was surprised
when they had to be
discriminated against by the cashier because they were racially
different.
Therefore, from this video, we get to understand how
American’s were racists
against in other races more than 100 years ago. We get to learn
that despite the
discrimination and biased treatment against the Japanese, their
resolve to stay and grow
in America was never collapsed. They stayed foot and faced all
the challenges but
ultimately remained in America. The moral lesson we can learn
from this video is that
even if one is facing challenges, really tough ones in life, one
should always stay focused
on their goals. The Japanese could have decided to leave
America and get back home,
however, they would have meant that they gave up and hence
could have not have

managed to accomplish their very first goal of migrating into
the United States.
Therefore, this video presents me with a historically rich
knowledge of how the Japanese
found their way into the United States more 100 ago and how
this community persevered
to grow despite the apparent racism against them by their fellow
American counterparts.
Asam100bb
Xinyu Shang
On the reading A Shocking Fact of Life the author gives a
recount of their
historical past and a trail of events on how she realized that she
was a Japanese and not a
Yankee. She does not admit that she is not a Japanese till
revealed to her by her parents.
The author is told by her mother, “Your father and I have
Japanese blood, and so do you,

too” (A shocking fact of life 4). The parents to the narrator had
migrated to the U.S to
look for greener opportunities, especially education. The
narrator says, “Mother and her
sister sailed into the port looking like exotic tropical butterflies
( A shocking fact of life
6). This statement shows that they looked like foreigners. Also,
the author gives a recount
of the Japanese culture and the lifestyle of their family. The
author says “on mother’s bed
lay a beautiful silk comforter patterned with turquoise, apple-
green, yellow and purple
Japanese parasols ( A shocking fact of life 10).
On the The Stubborn Twig the author gives an account of the
Japanese culture
and how it instilled discipline through the hard way. The
narrator is unwilling to undergo
the Japanese education system because it is tough compared to
American grammar. The
Japanese learning system is embedded in strict disciplinary
actions. The mother to
narrator tells him, “Your father and I received harsher
discipline than that in Japan . . .

not only from schoolteachers but also from our own parents
(The stubborn twig 26). The
narrator is being forced to adopt the Japanese culture, which is
unwilling to admit. She is
reluctant to bow down to hotel patrons. The narrator was
concerned with learning the
Japanese culture but rather was interested in detective
magazines. Although the narrator
is interested in detective work, the police in her neighborhood
have a wrong way of
handling residents. They are corrupt, something that is against
Japanese culture, which
propagates honesty. Like the title “The Stubborn Twig” the
father to the narrator is
stubborn not to give bribery to the police. One of the policemen
puts it that “Oh, so
you’re going to be stubborn about it. Maybe you want to explain
everything to the Judge,
Charlie” ( The stubborn twig 36).
On the Lon Kurashige: The problem of Biculturalism author
claims culture
recognition is one of the integral aspects of a community
because it brings a sense of

ownership and identification among the mass culture. Though
cultural recognition is
essential, it becomes a challenge in a foreign land. People of a
common language or
culture try to create factions to present them in the broad multi-
language spectrum. The
author states “Hayashi found deep ambivalence among second-
generation Protestants
about choosing American and Japanese culture . . . supporting
Japan’s aggression in East
Asia (Kurashige 1634). In this reading, the author gives the
struggle between Americans
and Japanese, whereby Americans wanted to assimilate Japanese
into the American
culture. Japanese were not into the idea of American
assimilationist because it did not
propagate Japanese imperialism. The Japanese intended to have
a cultural recognition in
the U.S as the American culture had.
On the Takao Ozawa vs. United States The process of obtaining
citizenship in the
U.S involves a broad spectrum of a legal framework. One can
become a U.S citizen by

birth, naturalization, or acquisition. Naturalization is the
process whereby a person not
born in the U.S voluntarily becomes a U.S citizen. The article
gives an account of what
grounds African natives, and Japanese would become U.S
citizens through naturalization
without discrimination. Before the revision of the naturalization
act, several acts such as
The Chinese Exclusion Act of May 6, 1882 (Ozawa v. United
States 6) excluded the
Chinese community from obtaining U.S citizenship through
naturalization.
Xinyu Shang
ASAM 100 BB
Reading Journal
The article, “In My World 1+1=3” by Yuki Kondo Shah gives
the experience of
Yuki Kondo who identifies as a multiracial. Yuki is a young
woman with a Bangladeshi
father and a Japanese mother. Yuki notes that when she was

young, living in Japan she
identified as a Japanese, however, upon relocating to the United
States when she was
seven, she struggled figuring out where she fits in. According to
Yuki, when growing up,
she always felt stuck between her two identities and she could
not clearly identify with
one side over the other. She notes that, “While I spent most of
my childhood being
Japanese and my college years identifying as a mixed-race
minority. I began my
professional career as an Asian America.” The experience of
Yuki, is one of many, where
it shows the dynamics of being Asian American in the United
States. Yuki chronicles the
conflicts that come with being a multiracial and the conflict that
comes with striking a
balance between the two races.
The article, “Who Studies The Asian American Movement? A
Historiographical
Analysis” by Diane Fujino studies the historiography of the
Asian American Movement.
The article focuses on the period from the late 1960s when
resistance by the Asian

Americans was regarded as a social movement to the 1970s
when the Asian American
Movement was on the decline. According to Fujino, the rise of
the Asian American
Movements was prompted by Asian revolutions, the Black
Power ideology and the Third
World. Such is because these events positioned the Asian
Americans as a model
minority. The AAM especially developed during the height of
Black Power and hence it
serves as a reflection of the radicalism that existed in the 1960s
and 1970s. The AAM
was championed by activists who sought to contest racism by
challenging the
racialization of the Asian Americans. Through their struggles,
these activists
demonstrated the existence of anti-Asian racism and also
challenged any sorts of
discrimination against the Asian Americans by advocating for a
more just society. Thus
helped to shape the pan-Asian and Third World identities.
Overall, the article offers a

very interesting account on how the Asian American Movement
played a major role in
bringing the concerns of the Asian Americans to light and in
fighting for better treatment
of the Asian Americans.
The article, “The Emergence of Yellow Power” by Gidra was
written in 1969
where it includes assertions of the Asian-American identity
based on the educational
experiences of different college students. The article thus serves
as the voice of the Asian
American Movement as it brings to light issues facing Asian
Americans that are often
sidelined by the mainstream media. The article is thus all about
self-expression and not
necessarily about stereotypes. Gidra allows for the different
authors to position cultural
and political issues in the United States within the larger Asian
American Movement.
Since the article is dominated by authors that are Asian
American in nature it focuses on
concerns like the incarceration of the Japanese Americans and
how each identity group of
the Asian Americans had its own unique experiences and dealt

with different struggles in
their struggle against the stigma imposed on them. By
discussing such concerns, the
authors discuss buried trauma and also express their hidden
emotions on the experiences
facing the Asian Americans. Overall, the article is very
insightful, it not only focuses on
the negative aspects that are associated with Asian Americans
rather it presents a new
perspective for the Gidra authors to acknowledge and embrace
their past, hence allowing
them to better reconcile their past, their present and their future.
Xinyu Shang
ASAM 100 BB
Reading Journal
The reading, “New York, New Life,” begins on page 70 and
introduces us to the
relationships or love life between Bill and Yuri. The main idea
from pages 70 to 72 is that

the love or relationships was at wartime where ladies were
hurriedly married and gave
full commitment to their husbands because they never knew if
their husbands would
come back. Many ladies were devastated by their men’s failure
to come up from the
wars. We see how Yuri kept on sending Bill letters as she
seduced him which led to their
hurried married within the 3 months. However, Yuri becomes
disappointed and annoyed
when the father-in-law asked the chaplain to postpone marriage
until she met him
describing the situation as Mr. Kochiyama’s condescension.
We learned that Bill’s father has to follow tradition which was
apparent in
samurai’s family which generally gave false pride in Yuri’s
viewpoint. Yuri was
opposed to the Japanese cultural life and said that the tradition
was biased to lower cadre
individuals. However, we also learned that this tradition
dictated what an “ideal wife”
would be, though Yuri remained ignorant of what it was to be
an “ideal wife” beyond
merely just saying that she hoped to be an “ideal wife” to Bill.

To Yuri, her main
objective is to help other people and hence views concerns of
financial management as
mundane/nuisance as she tells in the story offered on page 74-
75. What comes clear when
Yuri invited many soldiers for her brother to treat is that she
was ignorant and naïve
about the value of money.
Another idea was an apparent racial discrimination at
Hattiesburg (residential
discrimination) which affected Yuri’s personality as it
discriminated against Japanese
Americans who never welcomed including Black and Latino
soldiers. Yuri had to move
various times in Hattiesburg to get the house to live in at Earl
Finch (Godfather of the
442). This migratory experience of Yuri accounts for her
expanding awareness of racism
and race as she consciously engrossed her apprehensions
outwards making her to
constantly work as a Japanese American USO worker to find the
house for the Nisei

soldiers via her dedication and hard work which was
appreciated by Ishikawa. Yuri
played a key role as a promoter of the patriotic goalmouths of
the USO with the hope that
the Japanese American fight would ultimately open the doors
for the rest of her
community.
The marriage between Chiyo Ogata and Art brings the
comparison between
American and Japanese customs. We learn that Japanese custom
dictates that it remains
the duty of the firstborn son to care for the old parents whereas
American customs hold
that it is the daughter to care for an aging parent. Another
concern is the effects of the
postwar on Yuri where she could not even find a job because
she never belonged to a
major of a union in San Pedro as she awaited Bill’s return. She
could never find a job
because they were seen as Japanese and not as Americans. Yuri
was appreciated in the
reunion organized for her selfless work to help many people.

Xinyu Shang
ASAM 100 BB
Reading journal
The article, “Who Studies the Asian American Movement? A
Historiographical
Analysis” by Diane Fujino details the activism of Asian
Americans. The article is very
spectacular as it focuses on an area that has long been sidelined
which is the political
protest of the Asian Americans. In the article Fujino takes the
readers back to the late
1960s and early 1970s when the AAM (Asian American
Movement) gained traction and
was widely recognized as a social movement. The article notes
that the period between
the late 1960s and early 1970s was marked by activists
producing knowledge on the
existence of Asian Americans. The period between the late
1970s and late 1980s was
marked by a vacuum in Asian American Movement. The period
between the late 1980s

and late 1990s was dominated by a slow emergence in scholarly
works on Asian
American Movements and civil rights frameworks. The fourth
period from 2000 to the
present was marked by the full maturing of scholarly works
associated with Asian
American Movements which saw the connection of social,
political and national issues.
By exposing the different areas of struggle to the Asian
Americans the article helps to
bring to light major issues facing the Asian Americans like
racism, capitalism and sexism
not just abroad but also at home.
Unlike other historiographies, Fujino takes on a very unique
perspective by
including book chapters, dissertations and journal articles. The
inclusion of these research
studies helps to portray the significance of Asian Americans in
the Cold War. For
example Asian soldiers positioned by the American military
were fundamental to the
American empire building in the Asian Pacific region. Such
shows how the American

state officials attained global capitalist assimilation while
appealing to anti-colonialism
and antiracism hence supporting the position that
“decolonization was not antithetical to
the spread of U.S global power but intrinsic to it.” According to
Fujino, American shaped
the racialization of the Asian Americans, during the Cold War
where it rewarded
assimilation while disciplined Chinese and Korean radicals.
The article further addresses the problems of framing Asian
Americans in
education and related fields. It noted that the characterization of
Asian Americans as
model minorities or the oppressed minority only instills
problems in education and other
related fields. Overall, by focusing on the Asian American
Movement, Fujino seeks to
challenge racism by questioning the notion of racialization of
the Asian Americans. The
article is not so much a call to rescue but rather a depiction of
the struggles faced by the
Asian Americans and the call towards a more just society. The
article in my case is very

insightful as it beings to lights the efforts of the Asian
American Movement and how it
helped the Asian Americans to champion for better treatment of
themselves. The article is
significant in advocating for change and also in illustrating the
importance of doing away
with aspects like racism or discrimination as it marginalizes
certain ethnicities and makes
their integration into societal issues more difficult. Fujino did a
spending job with the
article and in portraying the efforts of AAM.
Asam100bb
Xinyu Shang
It has been a commonly held view that the Issei, even though
they had migrated to
the United States, held a strong patriotic sense for their own
country, especially in times
of crises or war. Some believe that it’s simply because they
were the first generation of

Japanese immigrants in the United States, while others view it
as a manifestation of their
accumulated anger. Although not being a unique case as the
likes of Irish, Polish ad
Jewish also largely supported their homeland, the Issei showed
their nationalism quite
strongly through even material means. In times of war, the Issei
made every possible
effort to support their homeland. For example, the use of
“comfort bags” as a token of
their appreciation and support was very common for Japanese
immigrants. Inspired by
this sentiment, the Japanese immigrants collected comfort bags
from their communities
throughout the United States and sent them to help their
homeland. However, this
contribution to the war soon took on other forms as the war
continued with no end in
sight. After the initial few years, it became a matter of
competition with the other
transnational Japanese communities as the Issei strove to be
recognized as the largest
contributors in the war.

The Issei made sure this was achieved by resorting to more
extreme methods such
as forcing even the reluctant and indifferent Japanese residents
to contribute to their
cause and feelings of nationalism. This behaviour especially
focused on the Nisai, since
they were born in the United States and didn't share the Issei's
patriotism for Japan.
However, this problem was also dealt with in the form of social
pressure. Though they
were now Americans by nationality, the Japanese immigrants
still lived in separate
communities and had their social structures and norms. This
fact was exploited by the
Issei, as they started taking records of all the donations given
by their residents. In their
social structure, due to the intense atmosphere of patriotism
driven by the Sino-Japanese
war, any individual not contributing to their cause was looked
down upon while those
that did rose in the social hierarchy. This phenomenon forced
even many of unwilling
and indifferent immigrants to donate even though they held no

ties to the war. Despite
their support of Japan in these times of crisis, it became
apparent to the Issei that their
country of residence didn’t see their homeland in a positive
light. They soon realized the
threat this posed when the danger of the Americans boycotting
Japanese exports, a
measure initiated by China, became clear. Again, motivated by
their feelings of
nationality and patriotism, the immigrants took it upon
themselves to “educate” the white
Americans on the full extent f the circumstances around the
Sino-Japanese War.
Even though the effort was sold in the image of their worry and
loyalty to Japan,
the immigrants were actually concerned about their
circumstances if the Americans
started viewing them in a bad light. Their main purpose was to
"educate" the population
of the United States by providing them with a new perspective
of the situation, one that
viewed Japan in a positive light. They showed this extensively
through forming
numerous committees, publishing journals, giving lectures in

various areas and even
educating the Nisai, who had little knowledge of their
homeland, of all they needed to
know in this effort.
The patriotic Issei felt compelled and free to take part in these
nationalistic
activities because of Japan's war with China alone. However,
later when America started
opposing their homeland as well, all the immigrants seized their
activities for the sake of
self-preservation. The issue had exceeded enough to risk their
own personal lives, which
outweighed their patriotic feeling.

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