If we are to save the future of our country and our education – we must demand credentials and academic achievement. For we short change everyone by bestowing credit where it is not due!!

Martin Roberge, quantitative analyst with Canaccord Genuity, said “nobody should be surprised” by the correction, but that it is a stark reminder that the TSX is essentially a split market between resource and non-resource sectors.

“The former group is down 5.9% this year compared with +5.1% for the latter. Unfortunately for Canadian investors, a bifurcated market is likely to prevail for a while,” he said.

Non-resource equities, which make up 55% of the market, will likely remain in a bull market and represent core/strategic holdings in portfolios, while resource equities (the other 45%) will stay in a bear market until China changes course through policy easing and returns to prior commodity consumption levels.

“Until then, shares in the energy and material sectors are tactical holdings which should be favoured when they are oversold and undervalued,” Mr. Roberge said.

If China’s economy were to suffer a hard landing, as some economists now forecast, TSX resource sector metrics could test 2008 lows, but Mr. Roberge argues this is premature.

In the meantime, investors should stick to gold and fertilizers over base metals. Gold at the moment is the most oversold and undervalued, and should provide protection from a volatile market. Fertilizers also benefit from being consumer-led commodities (even in a recession people still have to eat after all) and are less sensitive to some of the macro turbulence.

Also, farmer margins are widening thanks to falling fertilizer prices, suggesting more usage this spring, he said.

I am not going to display my mathematical proofs in this blog but I presume the explanation below would be enough to sketch out what is going on in Malaysia (not to include Non-Linear Lanchester Theory and N-Persons Game Theory):

The Theory “R-A-H-M-A-N” (6 Dimensional Alphabets)  has arrived to an end towards its destination of 13th Cycle of General Election (PRU-13). The next coming Prime Minister will be the 7th Prime Minister to be elected by the power of people. Fibonacci is here to explain that this coming Malaysian General Election, The PRU-13 is to accomplish the 13th cycle by choosing their 7th Prime Minister. Chaos is an Order But Without Periodicity. The Canonical Equations – Self-Perturbed Prime Numbers – Chaos and Turbulence – This going to be the Real Chaos within the sublimation of Non-Isotropic Turbulence.

The Spiral of Archimedes

Orbital Period 3 Bifurcation Diagram of Logistic Map – “Period 3 Implies Chaos”

Fibonacci Numbers

The sequence can also be extended to negative index n using the re-arranged recurrence relation

which yields the sequence of “negafibonacci” numbers satisfying

Thus the complete sequence is

F−8

F−7

F−6

F−5

F−4

F−3

F−2

F−1

F0

F1

F2

F3

F4

F5

F6

F7

F8

−21

13

−8

5

−3

2

−1

1

0

1

1

2

3

5

8

13

21

The Spiral of Fibonacci

This is the End of Fibonacci Retracement in Malaysia, The Hurst Exponent is Below 0.5 and Fractal Dimension Index is Above 1.5 – We Are now in The Region of Random Walk or Brownian Motion – The End of Chimera Tyrannical “Superpower” that to be Defeated By Bellerophon with The Help of Pegasus – The Canonical Equation is completed with the parameters and degree of freedom in equilibrium.

The Chimera (also Chimaera or Chimæra) ( /kɨˈmɪərə/ or /kaɪˈmɪərə/; Greek: Χίμαιρα, Khimaira, from χίμαρος, khimaros, “she-goat”) was, according to Greek mythology, a monstrous fire-breathing female creature of Lycia in Asia Minor, …

http://en.wikipedia.org/wiki/Chimera_%28mythology%29

Bersih 3.0: Bekas pendakwa kini peguam Anwar

KUALA LUMPUR: Bekas Ketua Pendakwaraya bagi kes liwat II, Datuk Mohd Yusuf Zainal Abiden (gambar) kini menyertai pasukan peguambela Datuk Seri Anwar Ibrahim dalam kes Bersih 3.0.

Tindakan ini merupakan satu tamparan hebat kepada Perdana Menteri, Menteri Dalam  Negeri dan Peguam Negara kerana orang terbaik mereka selama ini menyertai pasukan pembangkang.

Anwar bersama dengan Timbalan Presiden PKR, Azmin Ali dan bekas ahli majlis pimpinan pusat, Badrul Hisham Shaharin dihadapkan ke Mahkamah Sesyen Kuala Lumpur atas tuduhan mengambil bahagian dalam protes jalanan,  di bawah Akta Perhimpunan Aman.

http://bm.harakahdaily.net/index.php/headline/10482–bersih-30-bekas-pendakwa-kini-peguam-anwar

noun, plural tyr·an·nies.

******************************************************************************************************************************

Aku Memang Pencinta Wanita Namun Ku Juga Buaya

Sorry!, I am against LGBT (lesbian, gay, bisexual, and transgender)

“Strange days are these, in which, men are taught in falsehood school, and one who dares to tell the truth is at once called a LUNATIC AND FOOL”. – Socrates

Please give a look at the date April 9, 10 and 11 of 2012 (Related to Earthquake of Northern Sumatra), The Blue Shapes are Harmonic Cycles of Fibonacci Ratio (Golden Ratio)

- Anarchy, State and Utopia (A Book Written by Robert Norzick)

I received many questions from my readers about entropy, I would like to inform that ENTROPY is not the same CHAOS That We Had Discussed Over Here.

Update time = Thu Apr 12 9:42:56 UTC 2012

From The Atlantic (citing a Gallup servey): “Remember the good old days when everyone read really good books, like, maybe in the post-war years when everyone appreciated a good use of the semi-colon? Everyone’s favorite book was by Faulkner or Woolf or Roth. We were a civilized civilization. This was before the Internet and cable television, and so people had these, like, wholly different desires and attention spans. They just craved, craved, craved the erudition and cultivation of our literary kings and queens. Well, that time never existed. Check out these stats from Gallup surveys…”

“Time to sit tight. We believe the explosive phase of the equity market rally is over. At this stage of the recovery, history reveals that a period of market choppiness should develop, allowing for overbought conditions to correct,” Martin Roberge, quantitative analyst with Canaccord Genuity, said in a note.

That said, leading indicators still suggest the global economy will recover in the second half of the year, with a more self-sustaining U.S. economic recovery likely to constrain market corrections in the 4% to 6% range. As a result investors should instead be watching for buying opportunities as they arise.

“We believe investors should not play a correction and treat market dips as buying opportunities,” he said.

In Canada this will likely not come until China, as one of the country’s hungriest resource consumers, returns to more robust growth.

“We believe China-related groups (metals, machinery and aerospace) remain vulnerable until monetary reflation begins and/or the manufacturing sector stabilizes,” he said.

As well, if bonds do not rally in the next few weeks on the back of equity volatility, then it suggests the yield curve will normalize at steeper levels above 3% one year out.

Asset management pay, Dublin:

Source: Robert Walters 

Content analysis requires a researcher to identify categories, and then tally up the content into these categories to determine which topics are more frequent (Marks & Yardley, 2004). It is a methodical and unbiased tabulation of data (interview transcripts, articles, images, etc) (Franzosi, 2004). But this is not a simple quantitative exercise: the researcher uses her discretion to decide what fits in which category – but this discretion should be uniform and standardised (Marks & Yardley, 2004). But measuring the frequency is not enough, and doesn’t always produce valid results if the frequency of terms is not sufficiently contextualised (Marks & Yardley, 2004). The inferences made by the researcher can relate to the person/s who construct or consume a media text, or the text itself (Weber, 1990).

Thematic analysis:

Thematic analysis includes the type of coding used in content analysis, but also allows for greater discussion around themes which emerge when coding the data (Marks & Yardley, 2004). Themes can be obvious or subtly alluded to or inferred by the researcher (Marks & Yardley, 2004). They can also have different sources – if the researcher views the data in light of existing research, then she is coding deductively; if she constructs themes based on the data itself, she is coding inductively (Marks & Yardley, 2004).

Coding:

Both content and thematic analysis make use of coding – put simply, categorising information under certain headings (Marks & Yardley, 2004). These headings need to be determined by the research question and previous research, and not simply made up when looking at the data (Franzosi, 2004). The coding frame (group of codes/categories) is tailored so that it answers the research question (Marks & Yardley, 2004). Codes need to be specific – they can overlap slightly, but their boundaries need to be clearly defined and the categories shouldn’t be too broad, or the researcher won’t be able to separate different areas of the content effectively (Marks & Yardley, 2004) and the categories will become ambiguous (Weber, 1990). The reasons for coding and how content will be coded needs to be thoroughly explained to increase the reliability of the coding practice (Marks & Yardley, 2004). Smaller fragments of text (sentences and phrases) are easier to code than paragraphs, for example, which can include references to many different ideas and therefore fit in multiple categories (Weber, 1990).

Analysis and results:

Once all the data is coded, it can be analysed statistically to identify correlations and compare groups of content  (Marks & Yardley, 2004). Thematic analysis takes this a step further; high frequency items are discussed in depth (Marks & Yardley, 2004).

References:

Franzosi, R.P. (2004). Content analysis. In Hardy, M. A., & Bryman, A. (eds) Handbook of data analysis (pp.548-563). London: Sage Publications.

Marks, D.F., & Yardley, L. (2004). Content and thematic analysis. Research methods for clinical and health psychology (pp. 56-68). London: Sage.

Weber, R. P. (1990). Basic content analysis. Newbury Park, Calif: Sage Publications.

When I first the term, before I understood what it actually referred to in popular usage, I was thrilled. I thought the academy was finally getting its act together and that the digital humanities meant the things I was interested in: the humanities and technology. I was a computer nerd in high school, and I actually started my undergrad enrolled in Penn’s engineering school before I transferred to the liberal arts college and became an English major. It seemed like a total 180 to everyone else, but the change always made sense to me because I never saw the two fields as all that far apart. So a new academic approach to “digital humanities” sounded like exactly what I always wanted to do with my life: apply the analytic approaches and theoretical frameworks of humanities scholarship to digital technology and Internet culture.

But that’s not what “digital humanities” means. Or at least that’s not what’s really emphasized in the various nebulous definitions put forth. In general, digital humanities seems to refer to a methodology that applies quantitative analysis to humanistic studies. Franco Moretti may be the best known for this type of work, using massive data sets to extract macro-level insights from bodies of literature through what he terms “distant reading.” Since Moretti wasn’t actually *reading* a lot of the books in those data sets, lots of scholars got really mad and said computers were going to take over the English department and that it was the end of literary studies as we know them.

The whole thing seemed kind of ridiculous and overblown–on both sides of the aisle. Because Moretti started on his “distant reading” work before Google made it way easier for him. His grad students used to spend hours reading obscure Victorian novels to mine the data that could be pulled from digitized versions of the texts in minutes. It wasn’t that technology changed his approach to literary study: he changed his approach first and only later found a technology that complemented it.

Was Moretti’s scholarship an example of “digital humanities” even when he was doing the quantitative analysis by brute force? Is there any qualitative difference between the pencil-and-paper method and the computer-based one? If not, isn’t “digital humanities,” at least in this case, a pretty empty signifier?

A new set of tools does not, in and of itself, a new field of study make. An accountant who uses Quickbooks does not become a “digital accountant.” She’s still an accountant, except now she has digital tools to help her save time and do her job better. Literary studies have remained relatively undisturbed by digital technologies while they’ve seeped into a lot of other fields of inquiry. But that doesn’t mean that as soon as people start figuring out how to use them productively in their scholarship the whole department is going to be replaced by iPads. And by calling it “digital humanities” you’re creating a false distinction between two instances of the same type of academic scholarhsip.

S = E(R-Rf)/SD

Where
R is the expected return on Portfolio
Rf is the risk free rate
SD is the standard divition of the Portfolio

Over 2 comparable higher S is favorable. This shows that an investor prefer
1. Higher asset return over the benchmark rate.
2. Lower Standard Diviation.

Advantages:
1. Computable from any observed series of returns
2. Sharpe Ratio observes both Systemic & Idiosyncratic risk

Disadvantages:
1. The returns should be Normally distributed. Standard diviation only measures returns with symmetric distributions.
2. Should not be used to measure negative ratios as increasing the standard diviation of negative ratio decreases the risk which is not the case.
3. Ratio’s number is meaning less unless compared with several other type of portfolio with similar risk. (Dimention less)
4. Serial Correlation can overstate the Sharpe ratio.

Referances:

http://www.canadianfundwatch.com/

http://www.quantshare.com/

http://www.wikipedia.org/

http://www.investopedia.com/

(source, more about the watermelon stereotype here)

Measuring racism is a problem, as I’ve argued before. Asking people if they’re racist won’t work because they don’t answer this question correctly, and understandably so. This is due to the social desirability bias. Surveys may minimize this bias if they approach the subject indirectly. For example, rather than simply asking people if they are racist or if they believe blacks are inferior, surveys could ask some of the following questions:

• Do you believe God has created the races separately?
• What do you believe are the reasons for higher incarceration rates/lower IQ scores/… among blacks?
• Etc.

Still, no guarantee that bias won’t falsify the results. Maybe it’s better to dump the survey method altogether and go for something even more indirect. For example, you can measure

• racism in employment decisions, such as numbers of callbacks received by applicants with black sounding names
• racism in criminal justice, for example the degree to which black federal lower-court judges are overturned more often than cases authored by similar white judges, or differences in crime rates by race of the perpetrator, or juror behavior
• racial profiling
• residential racial segregation
• racist consumer behavior, e.g. reluctance to buy something from a black seller
• the numbers of interracial marriages
• the numbers and membership of hate groups
• the number of hate crimes
• etc.

newspaper clipping about an interracial marriage; February 10, 1955

(source)

A disadvantage of many of these indirect measurements is that they don’t necessarily reflect the beliefs of the whole population. You can’t just extrapolate the rates you find in these measurements. It’s not because some judges and police officers are racist that the same rate of the total population is racist. Not all people who live in predominantly white neighborhoods do so because they don’t want to live in mixed neighborhoods. Different crime rates by race can be an indicator of racist law enforcement, but can also hide other causes, such as different poverty rates by race (which can themselves be indicators of racism). Higher numbers of hate crimes or hate groups may represent a radicalization of an increasingly small minority. And so on.

Another alternative measurement system is the Implicit Association Test. This is a psychological test that measures implicit attitudes and beliefs that people are either unwilling or unable to report.

Because the IAT requires that users make a series of rapid judgments, researchers believe that IAT scores may reflect attitudes which people are unwilling to reveal publicly. (source)

Participants in an IAT are asked to rapidly decide which words are associated. For example, is “female” or “male” associated with “family” and “career” respectively? This way, you can measure the strength of association between mental constructs such as “female” or “male” on the one hand and attributes such as “family” or “career” on the other. And this allows you to detect prejudice. The same is true for racism. You can read here or here how an IAT is usually performed.

Yet another measurement system uses evidence from Google search data, such as in this example. The advantage of this system is that it avoids the social desirability bias, since Google searches are done alone and online and without prior knowledge of the fact that the search results will be used to measure racism. Hence, people searching on Google are more likely to express social taboos. In this respect, the measurement system is similar to the IAT. Another advantage of the Google method, compared to traditional surveys, is that the Google sample is very large and more or less evenly distributed across all areas of a country. This allows for some fine grained geographical breakdown of racial animus.

More specifically, the purpose of the Google method is to analyze trends in searches that include words like “nigger” or “niggers” (not “nigga” because that’s slang in some Black communities, and not necessarily a disparaging term). In order to avoid searches for the term “nigger” by people who may not be racially motivated – such as researchers (Google can’t tell the difference) – you could refine the method and analyze only searches for phrases like “why are niggers lazy”, “Obama+nigger“, “niggers/blacks+apes” etc. If you find that those searches are more common in some locations than others, or that they become more common in some locations, then you can try to correlate those findings with other, existing indicators of racism such as those cited above, or with historic indicators such as prevalence of slavery or lynchings.

More posts in this series are here.

It remains to be seen whether Tuesday’s huge rally, which saw the S&P 500 jump 3% and the S&P/TSX composite index climb 1.5%, will hold. However, one promising sign is the fact that the starting point of the market advance coincided with a much-depressed stock-to-bond ratio in Canada.

The TSX has lagged Canadian bonds by more than 20% year-over-year, according to Margin Roberge, portfolio strategist and quantitative analyst at Canaccord Genuity.

“In other words, Canadian stocks appear to be pricing a recession that we believe is unlikely in 2012,” Mr. Roberge said in a note to clients.

Should the current experience be another false-recession signal like in July 1988 and September 1998 – and he thinks it will – equities should outperform bonds in 2012.

In an effort to assess the longevity of this year-end event, the strategist looked at daily seasonality for the S&P/TSX composite in December and January to determine if there were any trading patterns that could isolate the Santa Claus rally.

Using data starting in 1969, he found that the final nine trading days of December and the first three of January have been positive for stocks. The TSX has returned 2.9% on average, while the average return is positive for all 12 trading days with probabilities greater than 50%.

However, beginning on the fourth trading day in January (Jan. 6, 2012), “it seems that the Grinch has reared its ugly head and has stolen some of the Santa Claus returns.”

Our fight-or-flight instincts may have served us well on the grand plains of Africa, but they only do us harm in financial markets, says Jim O’Shaughnessy, CEO and chief investment officer at Stamford, Conn.-based O’Shaughnessy Asset Management.

“While that may have saved us from the tigers, it is an awful thing to have happen when it is a financial decision being made,” he says. “People really need to understand that successful investing goes against every fibre in their being. People make exactly the wrong choice at exactly the wrong time, and they never seem to be able to recover from it.”

Mr. O’Shaughnessy, whose firm manages US$4.5-billion in assets, is responsible for seven funds at RBC Global Asset Management. This includes Canadian, U.S. value, U.S. growth and global mandates.

The leading expert in quantitative analysis is also the author of several books on investing, including the recently updated fourth edition of New York Times bestseller What Works on Wall Street.

Among the new additions to the book are sections on accounting variables and what works well at the sector level, as well as a chapter on neuroscience by Mr. O’Shaughnessy’s son Patrick.

“It definitely confirms what we found in our behavioural work, which was that, generally speaking, when people are making decisions about financial items, it is the emotional centres of the brain that fire, not the pre-frontal cortex,” he says.

The firm’s acquisition of the CRISP database, which goes back to 1926, helped demonstrate that 2008 was second to only 1931 among calendar year downturns.

The data also showed that February 2009 – just as Mr. O’Shaughnessy was calling the pullback in stocks a multidecade buying opportunity – marked the second-worst 10year period for U.S. securities. The first was May 1920.

He found that in the threeyear periods after these prolonged downturns, U.S. stocks have never experienced a negative return. The subsequent five-, seven-and 10-year periods also saw only positive results.

“The reason that happens is because at the bottom of these horrific 10 years, P/E ratios and other value measurements shrink, stocks become much cheaper, and dividend yields expand,” Mr. O’Shaughnessy says. “So in-vesting into a marketplace where you’re not paying a lot for every dollar of earnings or EBITDA/EV, and where you’re getting a much healthier dividend yield, it makes mathematical sense that those are the numbers that emerge.”

During a recent visit to Toronto he insisted that using long-term data is very simple. If you pay too much for a stock, you’re not going to do well. But how do investors factor in things like the eurozone crisis?

Mr. O’Shaughnessy insists the market has always had “what abouts” to worry about. For example, data from the 1930s showed that the Great Depression caused 25% of the workforce to be unemployed, while both the manufacturing base and land values were cut in half. Yet for investors who recognized that the market was prime for opportunity in 1931 and 1932, Mr. O’Shaughnessy says they would have gained 400% between 1931 and 1937.

His thesis applies the same way today: Disciplined and unemotional investors who use the data properly can beat the market handily over long market cycles – if they have the emotional capacity to withstand the ups and downs.

“It is very easy to say, but almost impossible to do,” Mr. O’Shaughnessy says. “Quants are the hyper-fundamentalists, all we pay attention to is the fundamental data. We don’t value opinion very highly because we realize how often it is wrong.”

So while many people talk about the “new normal” being characterized by persistently low returns, he thinks that is just as wrong as discussions of the “new economy” were back in the late 1990s when companies were being valued on how many hits their websites were getting.

“Whenever anything persists for the kind of length of time that this bear market has, people just believe it will inevitably continue,” Mr. O’Shaughnessy says, pointing to nearly flat markets in the 1968-1982 period and between the 1920s and 1950s.

“We have seen these periods before and we are unfortunately seeing one now,” he says. “However, we think we’re much closer to the end of that period than the beginning.”

Mr. O’Shaughnessy continues to believe markets are in the midst of a multi-year upward trend for equities, although volatility won’t likely disappear anytime soon. When factoring in valuations, dividend yields and even human behaviour, he thinks things are looking pretty good.

“There are solutions to the problems and I think people will come around to them. That’s why the rest of this math works,” Mr. O’Shaughnessy says of the U.S. political standstill over fiscal challenges. “It’s going to work even if you don’t get those solutions because of where we find ourselves in the balance sheet cycle with companies. But it’s going to work ridiculously well for equity investors even if we have half of the solutions in place.”

He also believes fixed income has reached the end of a 40-year bull market, citing the fact that several 20-year periods have seen negative real rolling returns for the asset class after adjusting for inflation.

“In many instances, people are giving money to the government that they know is going to be worth less when they get it back,” Mr. O’Shaughnessy says. “That is not an intelligent way to invest money.

• What if the holding cost percentage changes nextyear?  Will you or an analyst or whoeveruses this spreadsheet remember to change the formula?

• What if different items have different holdingcosts?  For example, obsolete items mightrequire a higher value due to the risk of write-offs.

• What if someone passes this spreadsheet along toa colleague working on a different product line, where the holding costpercentage should be 25% instead of 18%?

“The naive judgment of the dreamer on waking assumes that the dream – even if it does not come from another world – has at all events transported the dreamer into another world.”
The Interpretation of Dreams
~By Sigmund Freud

you tried to take away
my wish fulfillment you
dissected it bit by bit until
it became broken into pieces
of quantitative analysis
sterile bits of soul laid bare
upon your theoretical
frameworks

I allowed you to strip me
leaving my subconscious
naked the entire time believing
in your precepts trusting in
your self-professed science
becoming a hypothetical
experiment

how could you have known
anything of my candy colored
absurdities my twilight bathed
inspirations my laurel hopes my
Amazon desires you did not speak
my dream language your muteness
sliced my emotions with surgical
precision

if only you had cared to know
something of my autumnal eyes
my emerald amulet my perpetual
shores my beating waves my cerulean
depths you did not feel my swells
your resolute bias steeled
cool

© Pamela Rossow

Forex 2012: A View of Profits (We Generate Money Out of Chaos and Turbulence)

The Beauty of Fibonacci Numbers (Golden Ratio) in Fractal Markets and Self-Similarity Behavioral Analyses (Efficient Markets Hypothesis (EMH) and Financial Speculation)

References:

John D. Rawls ‘Justice as Fairness’, Philosophical Review, 1958

John D. Rawls, A Theory of Justice (Cambridge, MA: Harvard University Press, 1971)

David Hume, Enquires concerning the Human Understanding and concerning the Principles of Morals, Edited by L.E. Selby-Bigge (Oxford: Clarendron Press, 1962)

Aristotle, The Metaphysics, Translated with an Introduction by HUGH LAWSON-TANCRED. (Penguin Classics, 1998)

In simple words: “Why women can’t repay their loans  sometimes ?”

1.       The problem

A group meeting

The portfolio at risk (PAR30 for the experts) [that is the part of Fundacion Paraguaya’s loan portfolio that is at risk of not being repaid by the clients] is currently very low among group lending’s clients (women who borrow in groups of 15 to 30): less than 1%. That is particularly low compared to the 4% of individual lending. Yet, this percentage has recently been increasing. And worrisome, defaulting on a loan (ie not being able to repay it) now happens to women who are in their very first loan cycle, after only 1 month of taking out a credit.

So, is there something wrong with women themselves? Is the Paraguayan economy the one to blame? Is there something wrong with Fundacion Paraguaya’s credit methodology (be it the selection process or the groups’ follow up)?  Is there something wrong with microcredit in general? And what can be done to prevent it?

This was the agenda given to us a month ago: finding the causes and making recommendations to prevent defaults in the future.

2.       The method

Going at client's houses

Defining a methodology to proceed has been the hardest part of our study. It took us almost a month to have everybody agree upon it. After a few field tests, we came up with a mix of quantitative and qualitative tools. The purpose is to give Fundacion Paraguaya the largest overview of the problem. Therefore, we have decided to investigate 1. The figures; 2. Loan officers who know their clients more than anyone else; 3. Clients themselves.

Our study focuses on the Metropolitan area of Asuncion, because our data analysis showed us this is where 80% of the problem lies.

We have decided to conduct 15 qualitative interviews with every loan officer of the area to get their insights on what can lead women to difficult situations, and share their ideas to improve the loan follow up process to avoid those cases.

We have decided to interview nearly 30 women groups to have a qualitative discussion on what happened, and why they found themselves in a difficult situation. Especially, we want to understand why the group dynamic is not working. Because as you may (or not) know, in group lending, women are responsible for one another’s loans. That means if Sara cannot repay her weekly installment, the rest of the group is responsible for covering it, if they do not want to all default as a group and have fines to pay. And helping each other is what they usually do, because it happens to almost everyone during the course of a 4 months loan to encounter temporary difficulties (such as a kid being sick,…) preventing you from being able to pay that week. Although women are encouraged to have savings, they only have compulsory group savings with Fundacion Paraguaya, and it is really up to them to set money aside for difficult times (which they unfortunately rarely do).

On top of that, we collect quantitative data on each group member, to perform our analysis of causes, and profiles of women in arrears (whether there is actually a profile or some common characteristics of women who defaulted)

We have been conducting those interviews for 3 weeks now, testing our Spanish and Guarani skills (the other official language and often the mother tongue or only language of those women) and our resistance to temperatures above 90s (35° for Europeans)…

We do not have it all yet, but we do have some insights…

Follow this link for abstract

Date of publication: September 2011

Publication type: Journal article

In a nutshell: An analysis of the implementation and overall effectiveness of the Cancer Fast-track Programme in Catalonia, Spain. The programme aimed to reduce the time between suspicion of breast, colorectal and lung cancer and the start of initial treatment. Concludes that the programme has contributed to speeding up diagnostic assessment and treatment of patients with suspected cancer.

Length of publication: 7pages

Some important notes: Please contact your local NHS Library for the full text of the article. Follow this link to find your local NHS Library.

The modern world appears divided into two camps (no — not those who believe the world can be divided into two camps, and those who don’t): those who believe that man has mastered nature, and those who know better.

The first camp share two chief delusions:

1. That human beings — through the use of simulations, models, mathematics and other predictive techniques — can routinely make accurate predictions about the future.
2. That these predictions should be deployed — usually via the power of government — to advance society.