Youth Education and Employment in Mexico City: A Mixed-Methods Analysis

2020 ◽  
Vol 688 (1) ◽  
pp. 190-207
Author(s):  
Gabriela Sánchez-Soto ◽  
Andrea Bautista León
Keyword(s):  
Mexico City ◽  
Gainful Employment ◽  
Barriers To Education ◽  
Youth Education ◽  
Employment Barriers ◽  
Job Opportunities ◽  
Barriers To Employment ◽  
Education And Employment ◽  
Using Data ◽  
The Right

Research on young Mexicans tends to focus on their limited educational and occupational opportunities and the increasing extent to which they are not in education, employment, or training (NEET). In this article, we describe the prevalence and determinants of being NEET in Mexico City using data from the National Survey of Occupation and Employment and from forty in-depth interviews. Quantitative findings on the determinants of education and employment in this study are consistent with previous research. Barriers to education for those in NEET include low rates of admission to public universities, economic difficulties, family obligations, and difficulties connecting schooling and future employment. Barriers to employment include a lack of job opportunities, discrimination against inexperienced workers, and the undesirability of low-wage employment. Despite setbacks, respondents expressed a desire to attain education and gainful employment in the future, but many, especially the most educated, were willing to wait for the right university or job.

scholarly journals Off to Market: Neighborhood and Individual Employment Barriers for Women in 21st Century American Cities

2018 ◽  
Author(s):  
Timothy Haney
Keyword(s):  
Poverty Rate ◽  
Market Outcomes ◽  
Family Responsibilities ◽  
Reform Era ◽  
Logistic Regression Models ◽  
Employment Barriers ◽  
Barriers To Employment ◽  
Hours Of Work ◽  
Using Data ◽  
American Cities

This paper endeavors to create a better understanding of the barriers to employment faced by disadvantaged urban women in the post-welfare reform era. Using data from the Project on Devolution and Urban Change, a unique geographically-linked, longitudinal, multi-city set of survey data, logistic regression models weigh the relative importance of individual barriers to employment (poor health, childcare and family responsibilities, etc.) and contextual or neighborhood barriers to employment (poverty rate, joblessness rate, etc.) on labor market outcomes. Results reveal that several neighborhood characteristics are predictive of employment, including automobile access, female-headedness, vacancy, and disorder. Results suggest a more complex, nuanced interplay between neighborhood-level variables and individually-measured variables in preventing some women from obtaining both modestly paying employment with few allocated hours of work per week, and also better-paying jobs with more hours of work per week.

The Multiple-Vortex Structure of the El Reno, Oklahoma, Tornado on 31 May 2013

2018 ◽  
Vol 146 (8) ◽  
pp. 2483-2502 ◽  
Author(s):  
Howard B. Bluestein ◽  
Kyle J. Thiem ◽  
Jeffrey C. Snyder ◽  
Jana B. Houser
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Rapid Scan ◽  
X Band ◽  
Close Range ◽  
Formation And Evolution ◽  
Using Data ◽  
Secondary Vortices ◽  
The Right ◽  
Gust Front

Abstract This study documents the formation and evolution of secondary vortices associated within a large, violent tornado in Oklahoma based on data from a close-range, mobile, polarimetric, rapid-scan, X-band Doppler radar. Secondary vortices were tracked relative to the parent circulation using data collected every 2 s. It was found that most long-lived vortices (those that could be tracked for ≥15 s) formed within the radius of maximum wind (RMW), mainly in the left-rear quadrant (with respect to parent tornado motion), passing around the center of the parent tornado and dissipating closer to the center in the right-forward and left-forward quadrants. Some secondary vortices persisted for at least 1 min. When a Burgers–Rott vortex is fit to the Doppler radar data, and the vortex is assumed to be axisymmetric, the secondary vortices propagated slowly against the mean azimuthal flow; if the vortex is not assumed to be axisymmetric as a result of a strong rear-flank gust front on one side of it, then the secondary vortices moved along approximately with the wind.

scholarly journals Botulinum toxin injection changes resting state cerebellar connectivity in cervical dystonia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pavel Hok ◽  
Lenka Hvizdošová ◽  
Pavel Otruba ◽  
Michaela Kaiserová ◽  
Markéta Trnečková ◽  
...  
Keyword(s):  
Functional Mri ◽  
Resting State ◽  
Cervical Dystonia ◽  
Botulinum Neurotoxin ◽  
Botulinum Toxin Injection ◽  
Clinical Severity ◽  
Before And After ◽  
Positive Correlations ◽  
Using Data ◽  
The Right

AbstractIn cervical dystonia, functional MRI (fMRI) evidence indicates changes in several resting state networks, which revert in part following the botulinum neurotoxin A (BoNT) therapy. Recently, the involvement of the cerebellum in dystonia has gained attention. The aim of our study was to compare connectivity between cerebellar subdivisions and the rest of the brain before and after BoNT treatment. Seventeen patients with cervical dystonia indicated for treatment with BoNT were enrolled (14 female, aged 50.2 ± 8.5 years, range 38–63 years). Clinical and fMRI examinations were carried out before and 4 weeks after BoNT injection. Clinical severity was evaluated using TWSTRS. Functional MRI data were acquired on a 1.5 T scanner during 8 min rest. Seed-based functional connectivity analysis was performed using data extracted from atlas-defined cerebellar areas in both datasets. Clinical scores demonstrated satisfactory BoNT effect. After treatment, connectivity decreased between the vermis lobule VIIIa and the left dorsal mesial frontal cortex. Positive correlations between the connectivity differences and the clinical improvement were detected for the right lobule VI, right crus II, vermis VIIIb and the right lobule IX. Our data provide evidence for modulation of cerebello-cortical connectivity resulting from successful treatment by botulinum neurotoxin.

Barriers to Employment among TANF Applicants and Their Consequences for Self-Sufficiency

2007 ◽  
Vol 88 (3) ◽  
pp. 379-389 ◽  
Author(s):  
Amy Dworsky ◽  
Mark E. Courtney
Keyword(s):  
Longitudinal Study ◽  
Welfare Policy ◽  
Policy And Practice ◽  
Potential Barriers ◽  
Milwaukee County ◽  
Self Sufficiency ◽  
Barriers To Employment ◽  
Using Data

This article examines the prevalence of potential barriers to employment using data from a longitudinal study of 1,075 Milwaukee County parents who applied for assistance from Wisconsin's TANF program in 1999. It also examines whether those potential barriers were related to their subsequent employment and earnings. We find that many of these TANF applicants faced significant and often multiple barriers to employment. Moreover, these potential barriers were associated with both a reduction in their likelihood of being employed and lower earnings when they worked. The implications of these findings for welfare policy and practice are discussed.

scholarly journals Are Artificial Intelligence (AI) And Machine Learning (ML) Having An Effective Role In Helping Humanity Address The New Coronavirus Pandemic?

2020 ◽  
Vol 17 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Disease Outbreaks ◽  
Hospital Capacity ◽  
Data Engineering ◽  
Clinical Presentations ◽  
The Face ◽  
Effective Role ◽  
Using Data ◽  
The Right

COVID-19 has become a pandemic affecting the most of countries in the world. One of the most difficult decisions doctors face during the Covid-19 epidemic is determining which patients will stay in hospital, and which are safe to recover at home. In the face of overcrowded hospital capacity and an entirely new disease with little data-based evidence for diagnosis and treatment, the old rules for determining which patients should be admitted have proven ineffective. But machine learning can help make the right decision early, save lives and lower healthcare costs. So, there is therefore an urgent and imperative need to collect data describing clinical presentations, risks, epidemiology and outcomes. On the other side, artificial intelligence(AI) and machine learning(ML) are considered a strong firewall against outbreaks of diseases and epidemics due to its ability to quickly detect, examine and diagnose these diseases and epidemics.AI is being used as a tool to support the fight against the epidemic that swept the entire world since the beginning of 2020.. This paper presents the potential for using data engineering, ML and AI to confront the Coronavirus, predict the evolution of disease outbreaks, and conduct research in order to develop a vaccine or effective treatment that protects humanity from these deadly diseases.

scholarly journals A simulation-based approach to improve decoded neurofeedback performance

2018 ◽  
Author(s):  
Ethan Oblak ◽  
James Sulzer ◽  
Jarrod Lewis-Peacock
Keyword(s):  
Real Time ◽  
Brain Activity ◽  
Processing Parameters ◽  
Orientation Tuning ◽  
Design Parameters ◽  
Visual Orientation ◽  
Brain Functions ◽  
Simulation Based ◽  
Using Data ◽  
The Right

AbstractThe neural correlates of specific brain functions such as visual orientation tuning and individual finger movements can be revealed using multivoxel pattern analysis (MVPA) of fMRI data. Neurofeedback based on these distributed patterns of brain activity presents a unique ability for precise neuromodulation. Recent applications of this technique, known as decoded neurofeedback, have manipulated fear conditioning, visual perception, confidence judgements and facial preference. However, there has yet to be an empirical justification of the timing and data processing parameters of these experiments. Suboptimal parameter settings could impact the efficacy of neurofeedback learning and contribute to the ‘non-responder’ effect. The goal of this study was to investigate how design parameters of decoded neurofeedback experiments affect decoding accuracy and neurofeedback performance. Subjects participated in three fMRI sessions: two ‘finger localizer’ sessions to identify the fMRI patterns associated with each of the four fingers of the right hand, and one ‘finger finding’ neurofeedback session to assess neurofeedback performance. Using only the localizer data, we show that real-time decoding can be degraded by poor experiment timing or ROI selection. To set key parameters for the neurofeedback session, we used offline simulations of decoded neurofeedback using data from the localizer sessions to predict neurofeedback performance. We show that these predictions align with real neurofeedback performance at the group level and can also explain individual differences in neurofeedback success. Overall, this work demonstrates the usefulness of offline simulation to improve the success of real-time decoded neurofeedback experiments.

Unit-root tests for explosive behavior

2021 ◽  
Vol 21 (4) ◽  
pp. 999-1020
Author(s):  
Christopher F. Baum ◽  
Jesús Otero
Keyword(s):  
International Economic ◽  
Unit Root ◽  
American Statistical Association ◽  
Unit Root Tests ◽  
Statistical Association ◽  
International Economic Review ◽  
Augmented Dickey Fuller ◽  
Using Data ◽  
The Right ◽  
Rolling Windows

We present a new command, radf, that tests for explosive behavior in time series. The command computes the right-tail augmented Dickey and Fuller (1979, Journal of the American Statistical Association 74: 427–431) unitroot test and its further developments based on supremum statistics derived from augmented Dickey–Fuller-type regressions estimated using recursive windows (Phillips, Wu, and Yu, 2011, International Economic Review 52: 201–226) and recursive flexible windows (Phillips, Shi, and Yu, 2015, International Economic Review 56: 1043–1078). It allows for the lag length in the test regression and the width of rolling windows to be either specified by the user or determined using data-dependent procedures, and it performs the date-stamping procedures advocated by Phillips, Wu, and Yu (2011) and Phillips, Shi, and Yu (2015) to identify episodes of explosive behavior. It also implements the wild bootstrap proposed by Phillips and Shi (2020, Handbook of Statistics: Financial, Macro and Micro Econometrics Using R, Vol. 42, 61–80) to lessen the potential effects of unconditional heteroskedasticity and account for the multiplicity issue in recursive testing. The use of radf is illustrated with an empirical example.

STRUKTUR POLA ASUH ANAK TENAGA KERJA WANITA DI MADURA

2020 ◽  
Vol 13 (1) ◽  
pp. 40-68
Author(s):  
Heni Listiana
Keyword(s):  
Child Care ◽  
Migrant Workers ◽  
Data Extraction ◽  
Children Of Migrant Workers ◽  
Using Data ◽  
The Right ◽  
The Village ◽  
Source Of Information ◽  
Female Migrant

Discussions about children and female migrant workers (TKW) are always in interesting issue. Especially, related to child care. By using data extraction techniques such as observation, interviews, and documentation, it is known that parenting children of migrant workers in Madura has formed a new structure with the emergence of a second mother. There are three types of second mothers, namely grandmother,  bu de (mother's brother or sister), and sister of TKW's child. They carry out the role of mother, among them being a model of children's behavior that is easily observed and imitated, becomes an educator, becomes a consultant, and becomes a source of information. Nearly 77% of grandmothers become maternal substitutes for migrant workers' children. Grandmother is considered the right person to do childcare tasks. This structure is called the inner parenting structure. While the structure of outside parenting takes the form of community participation in child care, namely good neighbors, the attention of the village head (Klebun), and the environment of friends and schools.   Pembahasan tentang anak dan Tenaga Kerja Wanita (TKW) selalu menjadi isu yang menarik. Terutama yang berkaitan dengan pola asuh anak. Dengan menggunakan teknik penggalian data berupa observasi, wawancara, dan dokumentasi diketahui bahwa pola asuh anak TKW di Madura membentuk struktur baru dengan munculnya ibu pengganti (second mother). Ada tiga jenis ibu pengganti, yaitu nenek, bu de (kakak atau adik ibu), serta kakak dari anak TKW. Mereka menjalankan peran ibu diantaranya menjadi model tingkah laku anak yang mudah diamati dan ditiru, menjadi pendidik, menjadi konsultan, dan menjadi sumber informasi. Hampir 77% nenek menjadi sosok pengganti ibu bagi anak-anak TKW. Nenek dianggap sebagai sosok yang tepat untuk melakukan tugas-tugas pengasuhan anak. Struktur ini disebut dengan struktur pola asuh dalam. Sementara struktur pola asuh luar itu berwujud peran serta masyarakat dalam pengasuhan anak yaitu tetangga yang baik, perhatian kepala desa (Klebun), dan lingkungan teman dan sekolah.

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