Legal English Difficulties and Ways to Overcome

2021 ◽  
Vol 12 (4) ◽  
Author(s):  
O Shkurat ◽  
◽  
L Gartsunova ◽  
Keyword(s):  
Credit Card ◽  
Nonnative Speakers ◽  
Movement Analysis ◽  
Professional Activity ◽  
Real Problem ◽  
Legal Professionals ◽  
Complex Sentences ◽  
Legal Writing ◽  
Jury Instructions ◽  
Major Factors

Abstract. This article is devoted to the study of legal English and its main characteristics. Legal language is the language used by legal professionals in their professional activity. That fact that historically legal English developed separately from the plain English made it difficult for understanding by laypeople. People find the traditional legal writing in such documents as jury instructions, security disclosures, credit card agreements, apartment leases, cell phone contract, promissory note etc. Even native English speakers often complain that they cannot fully understand the documents written to give them information. The understanding of legal English has been a problem for centuries. It was the cause why the plain English movement arose in the 1970s. The purpose of the movement was to simplify the legal writing, make it simple and clear for average people. This problem arises not only for those people whose native language is English. Nonnative speakers also struggle with the complexity of English legal writing. Ukrainian legal professionals that engaged in the area of international, business or corporate law, have to draft documents in English. Sometimes that could be a real problem because unlike English and American legal schools, the majority of ours don't provide the separate course of English legal writing. The purpose of this article is to give practical advice to Ukrainian lawyers and interpreters, how, taking into account the peculiarities of legal English discourse, to draft documents in clear, simple and understandable way. Results of research. A lot of English and American scientists, lawyers as well as linguists, devoted their studies to the plain English movement. Analysis of their works shows that four major factors had influenced on the development of legal English: historical, sociological, political and jurisprudential. Owing to them legal English is full of words of foreign origin, archaisms, argots and terms of art. These factors also caused the frequent usage of formal words, common usage of common words with uncommon meaning, deliberate ambiguity in legal writing. The studies of legal writing by lawyers have focused basically on vocabulary. Linguists in their researchers have identified some other features: overly complex sentences, passives, nominalizations, multiple negations, archaisms and jargon, inappropriate document design. Described ways of simplifying legal English are quite easy to use. Taking into account tips mentioned in the article, legal professionals will be able to draft documents that will be clear and understandable for general public.

The Syntax of Cleft Sentences in Berber

1986 ◽  
Vol 10 (1) ◽  
pp. 53-77
Author(s):  
Moha Ennaji ◽  
Fatima Sadiqi
Keyword(s):  
Movement Analysis ◽  
Initial Position ◽  
Complex Sentence ◽  
Simple Sentence ◽  
Complex Sentences ◽  
Syntactic Description ◽  
Main Verb ◽  
Being Moved

This paper claims that the cleft sentence in Berber has many interesting aspects of both the simple and the complex sentences; however, this construction seems to derive from the basic simple sentence rather than from the complex sentence, since it involves just one main verb and behaves like an S, and not like an NP. The pragmatic implications of the cleft sentence reveal that the clefted constituents are generally contrasted with other constituents of the same structural status in some previous discourse. It is also argued that a WH-movement analysis of the cleft construction is intuitively plausible since clefting involves constituents being moved to the initial position of the sentence. The aim of this paper is to give a syntactic description of the cleft sentence in Berber.1 The reason for undertaking this study is that clefts in Berber pose interesting problems in terms of their structural possibilities, their pragmatic effect and their possible derivation.

scholarly journals Prediction of Credit Card Approval

2022 ◽  
Vol 11 (2) ◽  
pp. 1-6
Author(s):  
Harsha Vardhan Peela ◽  
◽  
Tanuj Gupta ◽  
Nishit Rathod ◽  
Tushar Bose ◽  
...  
Keyword(s):  
Machine Learning ◽  
Credit Card ◽  
Learning Model ◽  
Card Holder ◽  
Great Expectations ◽  
Machine Learning Model ◽  
Using Data ◽  
Major Factors ◽  
Tools And Techniques ◽  
Python Programming

Credit risk as the board in banks basically centers around deciding the probability of a customer's default or credit decay and how expensive it will end up being assuming it happens. It is important to consider major factors and predict beforehand the probability of consumers defaulting given their conditions. Which is where a machine learning model comes in handy and allows the banks and major financial institutions to predict whether the customer, they are giving the loan to, will default or not. This project builds a machine learning model with the best accuracy possible using python. First we load and view the dataset. The dataset has a combination of both mathematical and non-mathematical elements, that it contains values from various reaches, in addition to that it contains a few missing passages. We preprocess the dataset to guarantee the AI model we pick can make great expectations. After the information is looking great, some exploratory information examination is done to assemble our instincts. Finally, we will build a machine learning model that can predict if an individual's application for a credit card will be accepted. Using various tools and techniques we then try to improve the accuracy of the model. This project uses Jupyter notebook for python programming to build the machine learning model. Using Data Analysis and Machine Learning, we attempted to determine the most essential parameters for obtaining credit card acceptance in this project. The machine learning model we built gave an 86 % accuracy for predicting whether the credit card will be approved or not, considering the various factors mentioned in the application of the credit card holder. Even though we achieved an accuracy of 86%, we conducted a grid search to see if we could increase the performance even further. However, using both the machine learning models: random forest and logistic regression, the best we could get from this data was 86 percent.

High-Resolution Scanning Electron Microscopy of Biological Specimens

1988 ◽  
Vol 46 ◽  
pp. 186-187
Author(s):  
M. Müller ◽  
R. Hermann
Keyword(s):  
High Resolution ◽  
Freeze Drying ◽  
Room Temperature ◽  
Structural Information ◽  
Freeze Substitution ◽  
Critical Point Drying ◽  
Sem Study ◽  
Major Factors ◽  
Structural Preservation ◽  
Preparation Techniques

Three major factors must be concomitantly assessed in order to extract relevant structural information from the surface of biological material at high resolution (2-3nm).Procedures based on chemical fixation and dehydration in graded solvent series seem inappropriate when aiming for TEM-like resolution. Cells inevitably shrink up to 30-70% of their initial volume during gehydration; important surface components e.g. glycoproteins may be lost. These problems may be circumvented by preparation techniques based on cryofixation. Freezedrying and freeze-substitution followed by critical point drying yields improved structural preservation in TEM. An appropriate preservation of dimensional integrity may be achieved by freeze-drying at - 85° C. The sample shrinks and may partially collapse as it is warmed to room temperature for subsequent SEM study. Observations at low temperatures are therefore a necessary prerequisite for high fidelity SEM. Compromises however have been unavoidable up until now. Aldehyde prefixation is frequently needed prior to freeze drying, rendering the sample resistant to treatment with distilled water.

Trainable Children Can Learn Adjectives, Polars, and Prepositions!

1977 ◽  
Vol 8 (3) ◽  
pp. 181-187 ◽  
Author(s):  
Marlys Mitchell ◽  
Carolyn Evans ◽  
John Bernard
Keyword(s):  
Mentally Retarded ◽  
Chronological Age ◽  
Age Group ◽  
Achievement Gains ◽  
Active Involvement ◽  
Mentally Retarded Children ◽  
Locative Prepositions ◽  
Major Factors ◽  
Trainable Mentally Retarded

Twelve trainable mentally retarded children were given six weeks of instruction in the use of adjectives, polars, and locative prepositions. Specially prepared Language Master cards constituted the program. Posttests indicated that children in the older chronological age group earned significantly higher scores than those in the younger group. Children in the younger group made significant increases in scores, particularly in learning prepositions. A multisensory approach and active involvement in learning appeared to be major factors in achievement gains.

When Hearing Does Not Mean Understanding: On the Neural Processing of Syntactically Complex Sentences by Listeners With Hearing Loss

2021 ◽  
pp. 1-13
Author(s):  
Margreet Vogelzang ◽  
Christiane M. Thiel ◽  
Stephanie Rosemann ◽  
Jochem W. Rieger ◽  
Esther Ruigendijk
Keyword(s):  
Hearing Loss ◽  
Sentence Processing ◽  
Secondary Task ◽  
Sentence Comprehension ◽  
Inferior Frontal Gyrus ◽  
Normal Hearing ◽  
Cognitive Demands ◽  
Sentence Complexity ◽  
Complex Sentences ◽  
And Task

Purpose Adults with mild-to-moderate age-related hearing loss typically exhibit issues with speech understanding, but their processing of syntactically complex sentences is not well understood. We test the hypothesis that listeners with hearing loss' difficulties with comprehension and processing of syntactically complex sentences are due to the processing of degraded input interfering with the successful processing of complex sentences. Method We performed a neuroimaging study with a sentence comprehension task, varying sentence complexity (through subject–object order and verb–arguments order) and cognitive demands (presence or absence of a secondary task) within subjects. Groups of older subjects with hearing loss ( n = 20) and age-matched normal-hearing controls ( n = 20) were tested. Results The comprehension data show effects of syntactic complexity and hearing ability, with normal-hearing controls outperforming listeners with hearing loss, seemingly more so on syntactically complex sentences. The secondary task did not influence off-line comprehension. The imaging data show effects of group, sentence complexity, and task, with listeners with hearing loss showing decreased activation in typical speech processing areas, such as the inferior frontal gyrus and superior temporal gyrus. No interactions between group, sentence complexity, and task were found in the neuroimaging data. Conclusions The results suggest that listeners with hearing loss process speech differently from their normal-hearing peers, possibly due to the increased demands of processing degraded auditory input. Increased cognitive demands by means of a secondary visual shape processing task influence neural sentence processing, but no evidence was found that it does so in a different way for listeners with hearing loss and normal-hearing listeners.

Identifying Embedded and Conjoined Complex Sentences: Making it Simple

2007 ◽  
Vol 34 (Spring) ◽  
pp. 44-54 ◽  
Author(s):  
Susan A. Steffani ◽  
Louis A. Dachtyl, III
Keyword(s):  
Complex Sentences

Clinical Update: Understanding Causation: An Example Using Carpal Tunnel Syndrome

2007 ◽  
Vol 12 (6) ◽  
pp. 5-8 ◽  
Author(s):  
J. Mark Melhorn
Keyword(s):  
Risk Factors ◽  
Carpal Tunnel Syndrome ◽  
Carpal Tunnel ◽  
Legal Responsibility ◽  
Medical Evidence ◽  
Anatomic Structure ◽  
Legal Professionals ◽  
Compensation Systems ◽  
Tunnel Syndrome ◽  
Four Levels

Abstract Medical evidence is drawn from observation, is multifactorial, and relies on the laws of probability rather than a single cause, but, in law, finding causation between a wrongful act and harm is essential to the attribution of legal responsibility. These different perspectives often result in dissatisfaction for litigants, uncertainty for judges, and friction between health care and legal professionals. Carpal tunnel syndrome (CTS) provides an example: Popular notions suggest that CTS results from occupational arm or hand use, but medical factors range from congenital or acquired anatomic structure, age, sex, and body mass index, and perhaps also involving hormonal disorders, diabetes, pregnancy, and others. The law separately considers two separate components of causation: cause in fact (a cause-and-effect relationship exists) and proximate or legal cause (two events are so closely related that liability can be attached to the first event). Workers’ compensation systems are a genuine, no-fault form of insurance, and evaluators should be aware of the relevant thresholds and legal definitions for the jurisdiction in which they provide an opinion. The AMA Guides to the Evaluation of Permanent Impairment contains a large number of specific references and outlines the methodology to evaluate CTS, including both occupational and nonoccupational risk factors and assigning one of four levels of evidence that supports the conclusion.

Credit Card Processing

2007 ◽  
Vol 38 (11) ◽  
pp. 54
Author(s):  
JOSEPH S. EASTERN
Keyword(s):  
Credit Card

Role of pinnae and head movements in localizing pure tones 1The authors would like to thank Mr. Remi Humbert for implementing the experiment in Turbo Pascal and for his further assistance.

1999 ◽  
Vol 58 (3) ◽  
pp. 170-179 ◽  
Author(s):  
Barbara S. Muller ◽  
Pierre Bovet
Keyword(s):  
Sound Source ◽  
Head Movement ◽  
Movement Analysis ◽  
Head Movements ◽  
Sound Sources ◽  
Localization Accuracy ◽  
Sound Effects ◽  
Posterior Quadrant ◽  
Localization Performance ◽  
Pure Tones

Twelve blindfolded subjects localized two different pure tones, randomly played by eight sound sources in the horizontal plane. Either subjects could get information supplied by their pinnae (external ear) and their head movements or not. We found that pinnae, as well as head movements, had a marked influence on auditory localization performance with this type of sound. Effects of pinnae and head movements seemed to be additive; the absence of one or the other factor provoked the same loss of localization accuracy and even much the same error pattern. Head movement analysis showed that subjects turn their face towards the emitting sound source, except for sources exactly in the front or exactly in the rear, which are identified by turning the head to both sides. The head movement amplitude increased smoothly as the sound source moved from the anterior to the posterior quadrant.

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