“El mapa del mes” por el observatorio de Gauteng

La enseñanza superior y el ingreso medio de los hogares en Gauteng, Sudáfrica

The April 2016 Map of the Month focuses on the spatial distributions of tertiary education qualifications and median household income in Gauteng (Map 1). Government in the province has a mandate to foster greater social cohesion, but progress on this is frustrated by high levels of inequality. Numerous studies hypothesise and analyse a relationship between social inequality and levels of education (Dias & Posel, 2007; Mitra, 2011; Vergolini, 2012). However they rarely provide a spatial perspective on this relationship.

Map 1 illustrates the stark spatial correlation between areas of the province where there is a high proportion of the population with tertiary education qualifications and where there is a concentration of high median household income, and vice versa. Tertiary qualifications are mapped as the proportion of the population in each sub-place who, according to the 2011 census, held either a bachelor’s degree, post graduate diploma, honours degree, higher degree masters or PhD.

We provide a rather unusual representation of median household income through using ‘income lines’. This approach allows for a clearer spatial representation when income is overlaid with other socio-economic variables. Although unusual at first glance, the map should be viewed in the same way as one would view an elevation map. Whereas contour lines connect points with the same elevation above sea level, these ‘income lines’ connect points (sub-places) with the same median income level. We categorise the ‘income lines’ according to the 20th, 40th, 60th and 80th percentiles of income in the province. This approach clearly shows the spatial inequality in income across the province.

We represent the concentration of tertiary qualifications mainly because spatial differences are insignificant at the lower levels of education (No schooling, Gr 9 and Gr 12). We find that high proportions of populations (more than 10%) with no schooling occur in on 3.6% of sub-places. High proportions (more than 10%) with only grade 9 education occur in only 1.5% of sub-places. This suggests that basic education is highly accessible and residents have reasonable opportunities to continue their education to at least the middle of their secondary schooling. The concentrations of Grade 12 education as highest level of education is also relatively even.However, at higher education levels the disparities become clearer. The maps show that the spatial distribution of tertiary qualifications is highly unequal.

Map 2 and Map 3 separately show the spatial distribution of high concentrations of tertiary qualifications and median household income. The distribution of tertiary qualifications clearly shows that spatial clustering occurs around areas that are generally regarded as the ‘urban core’ of the province. Significantly lower levels of tertiary qualifications are found on the south-west periphery of the province, especially in the Merafong City, Randfontein, Westonaria and Emfuleni municipalities. Similar conclusions are true for the distribution of median household income. The urban core has significantly higher median household incomes, compared to the urban periphery. Clusters of higher median household incomes are also found outside of the urban core, in areas like Bronkhorstspruit, Carletonville, Cullinan and Heildelberg. This affirms the representation in map 1 that people with higher education qualifications and higher incomes are clustered around better urban amenities.

According to Dias & Posel (2007:1) “(f)ormal education was found to be a strong and significant predictor of income earned”. Our simultaneous representation of the distribution of tertiary education qualifications and median household income affirms this prediction, shows its spatial characteristics and emphasises the spatial clustering of relative wealth and deprivation in Gauteng. It is clear that a tertiary education qualification significantly boosts a household’s relative wealth and it therefore has important implications for a suitable response to social inequality in the province. The reasons for the spatial concentrations of higher qualifications could be attributed to a person’s ability to pass higher levels of education (although the average matric pass rate for the province, indicated in Vignette 28, is very high), but also the residential mobility gained by employment benefits or the processes of socio-economic succession. Ultimately, there is no doubt that unequal access to tertiary education (and subsequent unequal spatial distributions of qualifications) needs to be addressed if significant progress is to be made towards reduced social inequality and improved social cohesion.

References
Dias, R. & Posel, D., 2007: Unemployment, Education and Skills Constraints in Post-Apartheid South Africa, Development Policy Research Unit, DPRU Working Paper 07/120, ISBN: 978-1-920055-42-4.
Mitra, D., 2011: Pennsylvania’s Best Investment: The Social and Economic Benefits of Public Education, available online at: http://www.elc-pa.org/wp-content/uploads/2011/06/B…(Accessed 16/02/2016).
Vergolini, L., 2011: Social cohesion in Europe: How do the different dimensions of inequality affect social cohesion? International Journal of Comparative Sociology, 52 (3), 197 – 214.

Mapas y visualización del espacio (2a parte)

Continuando con la entrada anterior se muestra a continuación trabajos del Trimestre Lectivo I-15 usando la misma metodología de semestres anteriores los alumnos documentaron sus trayectorias de la casa la UAM y realizaron soluciones en base a un problema acotado dentro de la movilidad.

Cartel de movilidad
Recorridos de trayectorias con variables de modalidad de transporte, distancia, tiempo y costo calórico y financiero. La variable intangible se refiere al grado de estrés del viajero y la solución apunta a un sistema de viajes compartido a partir de puntos clave del trayecto con un sistema de identidad UAM que lo soporte. 
Final cartel
En este trabajo el equipo se enfocó en identificar los tipos de anuncios publicitarios que se encontraron en su trayecto así como la saturación de la información. La solución es un aplicación para compartir viajes de la comunidad universitaria pero se enfoca en que ambas partes obtengan un beneficio de el servicio. 
Cartel registro e intangible
Esta visualización de trayectorias registra el tipo de transporte, tiempo caminando y tiempo de espera así como el costo total de viaje por día de la semana y el mapa de intangibles se enfoca en distinguir los distintos tipos de sonidos que se encuentra el viajero en su camino.

Mapas y visualización del espacio (1a parte)

El siguiente trabajo contempla el trabajo de Laboratorio III de tres generaciones de alumnos de la carrera de Diseño Integral en la UAM Cuajimalpa. Los alumnos realizaron una exploración visual de su propia movilidad documentando la trayectoria de su casa al trabajo, posteriormente mapearon un atributo tangible o intangible que les llamó la atención durante el trayecto, como: (baches, luces, sonidos, anuncios, olores o actos violentos, graffiti etc.). Finalmente se centraron en resolver un problema a partir de la metodología del diseño para el cambio del comportamiento.

movilidad UAM Cuajimalpa
Este cartel se enfoca en el mapeo de 4 trayectorias de alumnos al campus universitario. El estado de las banquetas y puentes peatonales en la Av. Constituyentes y una solución relacionada con la detección de baches por un sistema de monitoreo ciclista.

 

Cartel_Final
Mapeo realizado en el trimestre de Invierno 2013 que muestra las modalidades de los alumnos de su hogar a universidad. Las zonas de conflicto (carga vehicular, incidentes y accidentes) en Av. Constituyentes, así como las zonas inseguras. El mapeo contempló la ubicación de “cruces” que la gente coloca cuando ocurre un accidente en la vía pública.

 

Cartel_Economico_50%
El trabajo que muestran los alumnos en este cartel es un comparativo de tiempo, distancia y costo de su trayecto así como las interfaces que se encontraron en el transcurso, la propuesta o solución se refiere a una Tarjeta única de transporte a partir de no traer cambio justo para la tarifa de pasajero en el transporte público.

 

EntregaCartel
El trabajo del equipo de “Onomatopeya vehicular” se enfocaba en documentar los sonidos emitidos por distintas fuentes durante el trayecto vehicular delos participantes así como una linea de tiempo fotográfica. La solución se refería a boletos de transporte coleccionables y mensajes con “emoticones” mostrando el humor de la gente en el tráfico.
Cartel_equipo_urbano
Además de mapear sus trayectorias en este ejemplo, el equipo de estudiantes UAM, explora distimtas maneras de mapear el graffiti urbano en la Av. Constituyentes utilizando distintos niveles de abstracción que van desde los códigos del color hasta los trazos de los “tags” o firmas.
Mapa-grafi-intangi2
El alumno Cristian López Cuevas hace una recopilación fotográfica del distintos graffitis en la Av. Constituyentes y Av. Observatorio (2013).

 

En el Trimestre lectivo de Invierno 2014 los alumnos realizaron un ejercicio similar al del año anterior, sólo que esta vez  ya estábamos ubicados en el nuevo Campus. Av. Vasco de Quiroga 4871, Col. Santa Fe. Del. Cuajimalpa de Morelos. Una característica que destacar en este ejercicio fue que se le pidió a los alumnos que copiaran el estilo gráfico de mapas turísticos o informativos en su propuesta.

cartel final
El equipo “Morado” además de las rutas del viaje, mapeo los de olores que encontraron durante sus trayectorias a partir de una clasificación de agradable, desagradable y circunstancial.  La solución de diseño considera un mapa de trayectos en tiempo real a la entrada de la Universidad.
Cartel final final
El equipo “Azúl” incluyó variables como: tipo de transporte, clima, costo, tiempo y ruta de viaje, además de explorar las texturas de distintos materiales con las que se encontraban.
Cartel_Mov_ROJO
El equipo”ROJO” documento el humor en el que venían durante su trayecto además de otras variables y la soluciones de diseño se basaron distintos lentes de DWI Toolkit de Dan Lockton

 

cartel final lab III
El equipo verde se centró en el mapeo de trayectorias con estados emocionales y se enfocaron en desarrollar una solución para la seguridad de la infraestructura y movilidad urbana con una aplicación que permita reportar baches, mal funcionamiento de señales y comportamiento de choferes del transporte urbano.
Proyecto Movilidad Equipo Amarillo c
En este ejemplo se comparan distintas variables en las rutas de los estudiantes a la universidad como: costo, tiempo, tipo de transporte, abordaje. Por otro lado se enfocan en el tipo de atuendo con respecto a la temperatura. La solución explora a una aplicación de viajes compartidos o “aventones”utilizando redes sociales, para la comunidad universitaria.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Viviendas de bajo impacto energético

Hola a todos les dejo esta liga que le pasé a Clara sobre un proyecto de la renovación de una cabaña con el propósito de que lograr un bajo impacto energético ambiental. Pongan atención en los  factores que consideran para que describan las viviendas en su trabajo. Me parece que esta ficha puede ser una buena manera se sistematizar las viviendas de todos en en su observación.

1999 Tofte Project
Tofte Project
Location: Tofte, Minnesota, USA
Goals: Occupant health
Energy efficiency
Resource efficiency
Environmental responsibility

Sustainable renovation of a 1947 cabin

Features: 1. Ecosystem: 96% of site functional
2. Stormwater: 100% on-site rainwater
retained and filtered
3. Transportation: short walk to town
4. Potable water use: not measured
5. Energy: 43% annual savings achieved
compared to ASHRAE 90.1 1999
baseline calculated by DOE2
6. Renewable Energy: 97.5% of total annual
energy usage is generated on site
7. Green Materials: low LCA impact
Recycled content: cellulose insulation, copper roof
Certified wood: plywood, framing lumber
Salvaged wood: cabin siding reused on garage,
interior and exterior finish wood
8. C & D waste: 95% of project waste recycled
9. Daylighting: 100% daylighting primary light source
10. Natural Ventilation: 100% of building for 60% of year.
Awards: AIA Minnesota Honor Award 2001
AIA COTE Top Ten Green Projects 2002
www.tofteproject.info
webapps.acs.carleton.edu/voice/features.php3?id=204
Tofte Project Website
Carleton College Voice
Size: 90 m²
975 s.f.
Lot: 24281 m²
261360 s.f.
Type: Renovation

Single-family 2 Bedroom

Setting: Rural Market: High income
Energy Sources: Grid electricity
Grid-connected photovoltaics
Bottled gas
Grid-connected wind
Wood

http://sealevel.ca/lowimpact/housing/action.lasso?-Response=search05.lasso&ID=1512

Por otro lado les copio el sitio para que vean la manera en que comunican el proyecto, específicamente la le da luz que le comentaba a Clara.  (la liga de abajo ya sirve)

http://www.tofteproject.us/

tofte_website3

El proyecto se muestra en el libro de Sarah Nettleton”The Simple Home: The Luxury of Enough”

Por último les dejo el portafolio del grupo que realizó el storytelling del proyecto.

http://erickassel.com/works/tofte-project/

La fuerza de voluntad tiene poco que ver con una buena alimentación 

Me parece interesante lo que IdeasTED nos muestra sobre estudios realizados en hábitos de buena alimentación, arrojan que no necesariamente están ligados a la fuerza de voluntad, sino que dependen de factores que no habíamos contemplado.
Una oportunidad para reflexionar sobre la economía del comportamiento.

We know surprisingly little about what we want to eat, and why. Researcher Brian Wansink has been leading thousands of studies to understand more.

Two decades ago, Brian Wansink accidentally hit on a revelation that would change the course of his career. He and his graduate students (he was a professor at Wharton at the time) were running a study on sustainable food packaging. In the middle of giving free bags of snacks to Philadelphia moviegoers to see if they noticed they ate more from big packages, they ran out of big bags and had to revert to teeny ones that held just 110 calories. And here’s what they found: People with four tiny bags ate half as much as those with one big 440-calorie bag — and said they’d pay 20 percent more for snacks if companies sold them in smaller packages. “So here’s the punch line,” he says: “You can make more money by selling less food.”

Since then, Wansink — now a professor of applied economics and management at Cornell, director of theCornell Food and Brand Lab, and author of books including Slim by Design — has run 1,200 studies, by his estimate, on eating behaviors. It turns out we are utterly at the mercy of our environment.

We know far less about our own eating habits than we think. Wansink has found that we make many more decisions about food than we’re aware of — typically more than 200 per day. You don’t just choose whether to eat cereal or eggs, or even which cereal to eat. You also choose how much cereal to pour, how much milk to add, whether to finish the bowl, whether to have seconds. “There’s all these decisions that we don’t even code,” he says.

All of these decisions are subject to environmental cues. “Most people think they’re master and commander of their own diet,” Wansink says. But contrary to popular belief (and a whole lot of New Year’s resolutions), he’s found that healthy eating has very little to do with willpower. In one study, Wansink and his colleagues set up a table in which two out of four bowls of soup continually refilled from an apparatus hidden underneath the table. Participants given the self-refilling bowls ate 73 percent more, but didn’t feel any more sated. “We tend to eat with our eyes and not our stomach, because our stomach is a crude measure of how much we’ve eaten,” Wansink explains.

Size matters. Ever heard of the “small plate movement”? That’s all Wansink. In study after study, he has found that the bigger the plate, the more we eat. This stems from an optical illusion — the same amount of food on a bigger plate looks smaller — as well as changes in consumption norms and our decreased ability to estimate calories in larger portions. Eveneducating people about the effects of using a bigger plate has no effect on how much they eat. This goes for beverages, too: even professional bartenders pour moreinto a short, wide glass than a tall, skinny one of equal volume.

Color matters. Just as we can be tricked by the size of a plate, we can be tricked by its color. In one study, people who ate off plates the same color as their food (pasta with Alfredo sauce on a white plate, or with marinara sauce on a red plate) served themselves 22 percent more than those randomly assigned to color-contrast dining. “When a person serves themselves, they’re not even really looking at what they’re serving. It’s usually in the peripheral part of their vision,” Wansink says. “One thing about the periphery is if something isn’t high-contrast, it blurs even more into the background.”

Visibility matters. The more you see, the more you eat. We eat twice as many candies from a clear container than from an opaque one. But this phenomenon can work for you, too — if you put healthy foods in sight. Wansink and co. photographedover 200 American women’s kitchens and found that those who had cereal on the counter weighed 20 pounds more than those who didn’t and those who had soft drinks out weighed 24 to 26 pounds more — but women with even a single piece of fruit out weighed an average of 13 pounds less. “It’s a powerful testimony about our ‘see-food’ diet,” Wansink says — har, har.

Placement matters. Not only do we eat more candy out of a clear container, but we eat more when it’s close by: just moving the container from the desk to six feet away noticeably reduces the amount people eat. But there are subtler effects of placement, too. A study of 213 patrons of an all-you-can-eat buffet found that those with lower BMIs were likelier to sit facing away from the food. And it turns out that where you sit in a restaurant can really impact what you order: Wansink’sresearch indicates that people who sit farthest from the front door eat fewer salads and are much more likely to order dessert, while those sitting near a window or at a high-top table order more salads and fewer desserts — likely, Wansink believes, because they feel more on display.

Surroundings matter. Our susceptibility to cues other than hunger to determine how much we eat goes beyond food, serving implements and even our situation in the restaurant to the very room we eat in. Wansink and his colleague transformed half of a Hardees into a fine-dining restaurant by dimming the lights and playing softer, slower music, and found that diners ate less, more slowly, and with more satisfaction.

But most of us simply do not believe the environment holds such power over our eating habits. “We all believe we’re smarter than a bowl. We all believe we’re smarter than the plate in front of us,” Wansink says. But in truth, chalking it up to our environment can release a lot of guilt, and be a huge relief. “It’s easier to be slim by design than to be slim by willpower,” he says. If you tweak your environment, it “ends up being done once, and typically follows you for the rest of your life.”

Photo: Stocksy.

Porqué los algoritmos serán las futuras estrellas del diseño

RATHER THAN USING SOFTWARE TO DRAW AND ANALYZE A DESIGNER’S VISION, AUTODESK WANTS TO USE COMPUTING POWER TO GENERATE THE IDEA ITSELF. WILL THIS RENDER DESIGNERS OBSOLETE?

The industrial designer of the future might just be a computer. The traditional design process can be a laborious one, full of iterations and tweaks to make a product just so. For years, design software makerAutodesk has been working on an alternative: a program that sorts through all the ways to make a product of specific measurements and then spits out the best option.

“In the past couple of years, we have experienced such an explosion of computing power that we can completely change the design equation,” says Autodesk chief technology officer Jeff Kowalski. Rather than using software to draw and analyze a designer’s vision, Autodesk wants to use that computing power to generate the idea itself—by running through a nearly infinite number of ways to build the same product.

Though still in the experimental phase, Autodesk has been working on computational design for the last seven years through research projects such as Project Dreamcatcher, a system that generates CAD geometry based on a list of functional requirements. This approach could prove especially effective in sectors where being light and strong are of the utmost importance—as with cars and airplanes, where extra pounds have a direct impact on fuel efficiency.

Here’s how it works. You type in a set of constraints for the product. Then an algorithm “will go through a nearly infinite set of results and head towards ones that are going to satisfy the designer,” Kowalksi explains. Say you want a chair that needs to support 200 pounds of weight and be two feet off the ground while using the least amount of material possible. The program might start off with 1,000 ways to make the same chair, and then intermix what it sees as the most effective components of those 1,000 chairs to make 1,000 new options. It can go through a million iterations of the same chair “in the time that it would take the designer to describe just one.” It can also suggest what type of material to use.

A computer isn’t constrained by preconceived notions of what a chair should look like. The example above, chosen from several designs the algorithm generated, has a curvy, slightly portly, webbed aesthetic, quite unlike our traditional conception of how a chair should look. Other options for making the same chair might include straighter legs, or just a single pedestal leg, but the algorithm is capable of generating a variety of different designs that all meet the required criteria.

It’s not a process that’s limited to making chairs. “This applies to buildings, bridges, automotive parts—everything we do where we have to draw things,” Kowalski explains. It could be used to design a lightweight underlying structure of, say, a bicycle, which could then be covered by a skin to give it a different look—so you’re not limited to the lattice aesthetic, even if that’s the most efficient material for that product.

Computational design isn’t aimed at replacing human insight. People are still better at making more subjective selections over issues such as aesthetics. But the program certainly does serve up a panoply of options and can help sort through some of the more tedious aspects of the design process.

[Images: Courtesy of Autodesk]

 

http://www.fastcodesign.com/3029756/why-algorithms-are-the-next-star-designers

8 actividades de emprendimiento que podemos enseñar a nuestros niños

8 entrepreneurial skills you should teach your kids [infographic]

Parents and guardians do many things to ensure the success of their charges, but after reading, ‘rithmetic, and not picking one’s nose in public, entrepreneurial skills can be tackled starting at a young age.

Here are a few lessons to get them off to a great start.

8-entrepreneurial-skills-you-should-teach-your-kids

Via Pumpic.

Educational infographics.

Posted by Kate Rinsema