position:research director

#Pro-savana

Vision

Improve the livelihood of inhabitants of #Nacala_Corridor through inclusive and sustainable agricultural and regional development.

Missions

1. Improve and modernise agriculture to increase productivity and production, and diversify agricultural production.

2. Create employment through agricultural investment and establishment of a supply chain.

Objective

Create new agricultural development models, taking into account the natural environment and socio-economic aspects, and seeking market-orientated agricultural/rural/regional development with a competitive edge.

Principles of ProSAVANA

1. ProSAVANA will be aligned with the vision and objectives of the national agricultural development strategy of Mozambique, the “Strategy Plan for the Agricultural Sector Development – 2011 – 2020 (PEDSA)”,

2. ProSAVANA supports Mozambican farmers in order to contribute to poverty-reduction, food security and nutrition,

3. Activities of ProSAVANA, in particular those involving the private sector, will be designed and implemented in accordance with Principles of Responsible Agricultural Investment (PRAI) and Voluntary Guidelines on the Responsible Governance of Tenure of Land, Fisheries and Forests,

4. Ministry of Agriculture and Food Security of Mozambique (MASA) and Local Government, in collaboration with Japan International Cooperation Agency (JICA) and the Brazilian Cooperation Agency (ABC), will strengthen dialogue and involvement of civil society and other appropriate parties,

5. Appropriate consideration will be given for mitigation of the environmental and social impacts, which might be provided through the activities under ProSAVANA.

Approaches of ProSAVANA

1. Incorporate the results of relevant studies on the natural conditions and socio-economic situations, to support the establishment of appropriate agricultural development models,

2. Increase agricultural productivity and production through appropriate measures, including improvement of farming systems, access to agricultural extension services including techniques and quality/quantity of inputs, value chain system and expansion of farmland,

3. Promote diversification of agricultural production, based on research results to increase profitability,

4. Provide opportunities to change from subsistence agriculture into a sustainable agriculture, with respect given to the farmers´ sovereignty,

5. Strengthen the capacity and the competitiveness of farmers and farmers’ organisations,

6. Enhance the enabling environment to promote responsible investments and activities, aiming to establish a win-win relationship between small-scale farmers and agribusiness firms,

7. Promote and strengthen local leading farmers to disseminate and scale-up development impacts,

8. Establish regional agricultural clusters and develop value chain systems,

9. Promote public and private partnership as one of the driving forces for inclusive and sustainable agricultural development.

▻http://www.prosavana.gov.mz
#Pro_savana #land_grabbing #terres #Mozambique #accaparement_de_terres

ping @odilon

Apparemment, le programme a été arrêté avant d’être implémenté.
Programme qui avait été promu par #Lula

’Fiction is outperforming reality’: how YouTube’s algorithm distorts truth | Technology | The Guardian
►https://www.theguardian.com/technology/2018/feb/02/how-youtubes-algorithm-distorts-truth

https://i.guim.co.uk/img/media/6ca9c73956bff72fb83f27568e97c88053b36879/0_384_5760_3456/master/5760.jpg?w=1200&h=630&q=55&auto=format&usm=12&fit=crop&crop=faces%2Centropy&bm=normal&ba=bottom%2Cleft&blend64=aHR0cHM6Ly91cGxvYWRzLmd1aW0uY28udWsvMjAxOC8wMS8zMS9mYWNlYm9va19kZWZhdWx0LnBuZw&s=083cd38b1e317eb1a0ed52bcde1ee065

There are 1.5 billion YouTube users in the world, which is more than the number of households that own televisions. What they watch is shaped by this algorithm, which skims and ranks billions of videos to identify 20 “up next” clips that are both relevant to a previous video and most likely, statistically speaking, to keep a person hooked on their screen.

Company insiders tell me the algorithm is the single most important engine of YouTube’s growth. In one of the few public explanations of how the formula works – an academic paper that sketches the algorithm’s deep neural networks, crunching a vast pool of data about videos and the people who watch them – YouTube engineers describe it as one of the “largest scale and most sophisticated industrial recommendation systems in existence”.

Lewd and violent videos have been algorithmically served up to toddlers watching YouTube Kids, a dedicated app for children. One YouTube creator who was banned from making advertising revenues from his strange videos – which featured his children receiving flu shots, removing earwax, and crying over dead pets – told a reporter he had only been responding to the demands of Google’s algorithm. “That’s what got us out there and popular,” he said. “We learned to fuel it and do whatever it took to please the algorithm.”

During the three years he worked at Google, he was placed for several months with a team of YouTube engineers working on the recommendation system. The experience led him to conclude that the priorities YouTube gives its algorithms are dangerously skewed.

“YouTube is something that looks like reality, but it is distorted to make you spend more time online,” he tells me when we meet in Berkeley, California. “The recommendation algorithm is not optimising for what is truthful, or balanced, or healthy for democracy.”

Chaslot explains that the algorithm never stays the same. It is constantly changing the weight it gives to different signals: the viewing patterns of a user, for example, or the length of time a video is watched before someone clicks away.

The engineers he worked with were responsible for continuously experimenting with new formulas that would increase advertising revenues by extending the amount of time people watched videos. “Watch time was the priority,” he recalls. “Everything else was considered a distraction.”

The software Chaslot wrote was designed to provide the world’s first window into YouTube’s opaque recommendation engine. The program simulates the behaviour of a user who starts on one video and then follows the chain of recommended videos – much as I did after watching the Logan Paul video – tracking data along the way.

It finds videos through a word search, selecting a “seed” video to begin with, and recording several layers of videos that YouTube recommends in the “up next” column. It does so with no viewing history, ensuring the videos being detected are YouTube’s generic recommendations, rather than videos personalised to a user. And it repeats the process thousands of times, accumulating layers of data about YouTube recommendations to build up a picture of the algorithm’s preferences.

Over the last 18 months, Chaslot has used the program to explore bias in YouTube content promoted during the French, British and German elections, global warming and mass shootings, and published his findings on his website, Algotransparency.com. Each study finds something different, but the research suggests YouTube systematically amplifies videos that are divisive, sensational and conspiratorial.

It was not a comprehensive set of videos and it may not have been a perfectly representative sample. But it was, Chaslot said, a previously unseen dataset of what YouTube was recommending to people interested in content about the candidates – one snapshot, in other words, of the algorithm’s preferences.

Jonathan Albright, research director at the Tow Center for Digital Journalism, who reviewed the code used by Chaslot, says it is a relatively straightforward piece of software and a reputable methodology. “This research captured the apparent direction of YouTube’s political ecosystem,” he says. “That has not been done before.”

I spent weeks watching, sorting and categorising the trove of videos with Erin McCormick, an investigative reporter and expert in database analysis. From the start, we were stunned by how many extreme and conspiratorial videos had been recommended, and the fact that almost all of them appeared to be directed against Clinton.

Some of the videos YouTube was recommending were the sort we had expected to see: broadcasts of presidential debates, TV news clips, Saturday Night Live sketches. There were also videos of speeches by the two candidates – although, we found, the database contained far more YouTube-recommended speeches by Trump than Clinton.

But what was most compelling was how often Chaslot’s software detected anti-Clinton conspiracy videos appearing “up next” beside other videos.

Tufekci, the sociologist who several months ago warned about the impact YouTube may have had on the election, tells me YouTube’s recommendation system has probably figured out that edgy and hateful content is engaging. “This is a bit like an autopilot cafeteria in a school that has figured out children have sweet teeth, and also like fatty and salty foods,” she says. “So you make a line offering such food, automatically loading the next plate as soon as the bag of chips or candy in front of the young person has been consumed.”

Once that gets normalised, however, what is fractionally more edgy or bizarre becomes, Tufekci says, novel and interesting. “So the food gets higher and higher in sugar, fat and salt – natural human cravings – while the videos recommended and auto-played by YouTube get more and more bizarre or hateful.”

But why would a bias toward ever more weird or divisive videos benefit one candidate over another? That depends on the candidates. Trump’s campaign was nothing if not weird and divisive. Tufekci points to studies showing that “field of misinformation” largely tilted anti-Clinton before the election. “Fake news providers,” she says, “found that fake anti-Clinton material played much better with the pro-Trump base than did fake anti-Trump material with the pro-Clinton base.”

She adds: “The question before us is the ethics of leading people down hateful rabbit holes full of misinformation and lies at scale just because it works to increase the time people spend on the site – and it does work.”

About half the videos Chaslot’s program detected being recommended during the election have now vanished from YouTube – many of them taken down by their creators. Chaslot has always thought this suspicious. These were videos with titles such as “Must Watch!! Hillary Clinton tried to ban this video”, watched millions of times before they disappeared. “Why would someone take down a video that has been viewed millions of times?” he asks.

I contacted Franchi to see who was right. He sent me screen grabs of the private data given to people who upload YouTube videos, including a breakdown of how their audiences found their clips. The largest source of traffic to the Bill Clinton rape video, which was viewed 2.4m times in the month leading up to the election, was YouTube recommendations.

The same was true of all but one of the videos Franchi sent me data for. A typical example was a Next News Network video entitled “WHOA! HILLARY THINKS CAMERA’S OFF… SENDS SHOCK MESSAGE TO TRUMP” in which Franchi, pointing to a tiny movement of Clinton’s lips during a TV debate, claims she says “fuck you” to her presidential rival. The data Franchi shared revealed in the month leading up to the election, 73% of the traffic to the video – amounting to 1.2m of its views – was due to YouTube recommendations. External traffic accounted for only 3% of the views.

Franchi is a professional who makes a living from his channel, but many of the other creators of anti-Clinton videos I spoke to were amateur sleuths or part-time conspiracy theorists. Typically, they might receive a few hundred views on their videos, so they were shocked when their anti-Clinton videos started to receive millions of views, as if they were being pushed by an invisible force.

In every case, the largest source of traffic – the invisible force – came from the clips appearing in the “up next” column.

#YouTube #Algorithme_recommendation #Politique_USA #Elections #Fake_news

Why Math Is the Best Way to Make Sense of the World | Quanta Magazine
▻https://www.quantamagazine.org/why-math-is-the-best-way-to-make-sense-of-the-world-20170911

https://d2r55xnwy6nx47.cloudfront.net/uploads/2017/09/RGoldin_520x292.jpg

In 2004, she became the research director of George Mason’s Statistical Assessment Service, which aimed “to correct scientific misunderstanding in the media resulting from bad science, politics or a simple lack of information or knowledge.” The project has since morphed into STATS (run by the nonprofit Sense About Science USA and the American Statistical Association), with Goldin as its director. Its mission has evolved too: It is now less of a media watchdog and focuses more on education. Goldin and her team run statistics workshops for journalists

#maths #stats #journalisme

Cultural Anthropologist Mimi Ito on Connected Learning, Children, and Digital Media - YouTube
▻https://www.youtube.com/watch?v=xuV7zcXigAI

Ajoutée le 4 août 2011

Mimi Ito is a cultural anthropologist and expert in the field of digital media and learning, focusing on children and youth’s changing relationships to media and communications. She recently completed the Digital Youth Project, a landmark study supported by the MacArthur Foundation of the ways youth use new media. In September 2010, she was appointed as the John D. and Catherine T. MacArthur Foundation Chair in Digital Media and Learning at UC Irvine.

Ito emphasizes the need to put aside prejudices against new media in order to harness their potential as learning tools: “I think there’s a more general perception in the culture around new media [...] that it is inherently a space that is hostile to learning. And that’s a perception that I think we really need to work against.” (4:46) “We know that the learning outside of school matters tremendously for the learning in school. [...] The question is: how can we be more active about linking those two together?” she adds. (5:33)

Mimi Ito is a Professor in Residence at the Department of Anthropology and the Department of Informatics at the University of California, Irvine, and serves as Research Director of the Digital Media and Learning Research Hub in the system-wide University of California Humanities Research Institute. To find out more about the Connected Learning focus of the Digital Media and Learning Research Hub, please visit ▻http://connectedlearning.tv/what-is-c....

#Mimi_Ito #Education #Culture_participative

Algorithmic trading could be to blame for pound’s ‘flash crash’ | New Scientist
▻https://www.newscientist.com/article/2108386-algorithmic-trading-could-be-to-blame-for-pounds-flash-crash

Kathleen Brooks, research director at spreadbetter City Index, said: “Apparently it was a rogue algorithm that triggered the sell-off after it picked up comments made by the French President, Francois Hollande, who said if Theresa May and co want hard Brexit, they will get hard Brexit.”

Scholars in solidarity with Ismail Alexandrani

Ismail Alexandrani was detained by Egyptian authorities on November 30th as he was coming back to his country to visit his sick mother. Alexandrani is one of Egypt’s brightest young researchers, who has spent the last few years doing ground-breaking work on the marginalized areas of Egypt – a blind spot in academic studies of the country – as well as on political Islam. His articles have featured in numerous publications and have been presented in international academic conferences, and they have earned him awards and fellowships. In his work, he has constantly demonstrated a genuine intellectual independence. He is a well respected member of the academic community, and someone we personally enjoyed working with. Alexandrani’s arrest is a repression of free speech and should be condemned. We hope that he will be released promptly and return to his friends and to the research community.

First signatures
Francois Burgat, Research Director, CNRS (Centre National pour la Recherche Scientifique). Vincent Geisser, Research Director, CNRS. Alain Gresh, Le Monde Diplomatique. Miriam Catusse, Director of Contemporary Studies, IFPO (Institut Français du Proche–Orient). Claire Beaugrand, Researcher, IFPO. Nicolas Dot-Pouillard, Researcher, IFPO. Laurent Bonnefoy, Researcher, CERI/Sciences Po. Matthieu Rey, Researcher, College de France. Stéphane Lacroix, Associate Professor, Sciences Po. Mounia Bennani-Chraïbi, Professor, Lausanne University.
Ellen Lust, Professsor, Yale and Gottenberg. Gibert Achcar, SOAS. John Chalcraft, LSE. Asef Bayat, University of Illinois
Khaled Fahmy Professor, AUC. Rabab al Mahdi, Professor, AUC.

▻http://freealexandrani.wesign.it/ar

How to Feed the World
▻http://www.nytimes.com/2013/10/15/opinion/how-to-feed-the-world.html?ref=opinion&_r=0&pagewanted=print

According to the ETC Group, a research and advocacy organization based in Ottawa, the industrial food chain uses 70 percent of agricultural resources to provide 30 percent of the world’s food, whereas what ETC calls “the peasant food web” produces the remaining 70 percent using only 30 percent of the resources.

In fact if you define “productivity” not as pounds per acre but as the number of people fed per that same area, you find that the United States ranks behind both China and India (and indeed the world average), and roughly the same as Bangladesh, because so much of what we grow goes to animals and biofuels. (Regardless of how food is produced, delivered and consumed, waste remains at about one third.) Thus, as the ETC’s research director, Kathy Jo Wetter, says, “It would be lunacy to hold that the current production paradigm based on multinational agribusiness is the only credible starting point for achieving food security.” This is especially true given all of its downsides.

As Raj Patel, a fellow at the Institute for Food and Development Policy, puts it, “The playing field has been tilted against peasants for centuries, and they’ve still managed to feed more people than industrial agriculture. With the right kinds of agroecological training and the freedom to shape the food system on fair terms, it’s a safe bet that they’ll be able to feed themselves, and others as well.”

Yet obviously not all poor people feed themselves well, because they lack the essentials: land, water, energy and nutrients. Often that’s a result of cruel dictatorship (North Korea) or war, displacement and strife (the Horn of Africa, Haiti and many other places), or drought or other calamities. But it can also be an intentional and direct result of land and food speculation and land and water grabs, which make it impossible for peasants to remain in their home villages. (Governments of many developing countries may also act as agents for industrial agriculture, seeing peasant farming as “inefficient.”)

The result is forced flight to cities, where peasants become poorly paid laborers, enter the cash market for (increasingly mass produced) food, and eat worse. (They’re no longer “peasants,” at this point, but more akin to the working poor of the United States, who also often cannot afford to eat well, though not to the point of starvation.) It’s a formula for making not only hunger but obesity: remove the ability to produce food, then remove the ability to pay for food, or replace it with only one choice: bad food.

It’s not news that the poor need money and justice. If there’s a bright side here, it’s that the changes required to “fix” the problems created by “industrial agriculture” are perhaps more tractable than those created by inequality.

#faim