The Origin of Species & Other Poems

Ernesto Cardenal, The Origin of Species and Other Poems,
ISBN 0896726894 Publisher: Texas Tech Press, U.S., 2011

THE ORIGIN OF THE SPECIES (Excerpt)

That all life on earth
should come from a single cell:
the great mystery
Everyone from a single ancestor
a universe still creating itself

one like a cow entered the sea
and became the whale
Fish or mammal?
Or mammal and fish
To Linnaeus a mammal
with a heart and lungs
and eyelashes that move
but with aquatic habits

By adapting to the environment
gradually
another species
fins of fish develop
into paws of invertebrates
why is one a parrot
and another a tiger
once there were no brains
now there are billions
there was no leaf
now everything is green
From a single cell
trees animals you
all brothers
we are all a modification of another
the bird wing was dinosaur’s paw ………….

OBSERVATION: How do we define the poet? The true poet lives, linked to the world, to life, to being human. Those poets who leave an indelible mark on the history of human thought offer us a glimpse into what is possible, what is truly possible when the human organism functions at its peak potential. Find this book, read it, ponder it, absorb it, learn from it!

FROMM: Necrophilous

FROMM, Erich, The Anatomy of Human Destructiveness, Holt, Rinehart, Winston, 1973.

“The term “necrophilous” to denote a character trait rather than a perverse act in the traditional sense, was used by the Spanish philosopher Miguel de Unamuno in 1936 on the occasion of a speech by nationalist general Millan Astray at the University of Salamanca, where Unamuno was rector at the beginning of the Spanish Civil War. The general’s favorite motto was Viva la Muerte! (“Long live death!”) and one of his followers shouted it from the back of the hall. When the general had finished his speech, Unamuno rose and said:

“Just now I heard a necrophilous and senseless cry: “Long live death!” And I, who have spent my life shaping paradoxes which have aroused the uncomprehending anger of others, I must tell you, as an expert authority, that this outlandish paradox is repellent to me. General Millan Astray is a cripple. Let it be said without any slighting undertone. So was Cervantes. Unfortunately there are too many cripples in Spain just now. And soon there will be even more of them if God does not come to our aid. It pains me to think that General Millan Astray should dictate the pattern of mass psychology. A cripple who lacks the spiritual greatness of a Cervantes is wont to seek ominous relief in causing mutilation around him. (M. de Unamuno, 1936.)

At this Millan Astray was unable to restrain himself any longer. “Abajo la inteligencia! (“Down with intelligence!”) he shouted. “Long life death!” There was a clamor of support for this remark from the Falangists. But Unamuno went on: This is the temple of the intellect. And I am the high priest. It is you who profane its sacred precincts. You will win, because you have more than enough brute force. But you will not convince. For to convince you need to persuade. And in order to persuade you would need what you lack: Reason and Right in the struggle. I consider it futile to exhort you to think of Spain. I have done. (M. de Unamuno, 1936.)

OBSERVATION: Freud’s theory of life and death instincts are rooted in the idea that man’s striving for life and death are two of the most fundamental principles in man. “Necrophilia in the characterological sense can be described as the passionate attraction to all that is dead, decayed, putrid, sickly; it is the passion to transform that which is alive into something unalive; to destroy for the sake of destruction; the exclusive interest in all that is purely mechanical. It is the passion “to tear apart living structures.” (H. von Hentig, 1964.) How is it that human destructiveness persists, after the recognition of the tragedy and horror it brings to human life? How is it that awareness, and the application of ethical and moral behavior have not become the standard by which all human behavior moves forward? Life, or Death?

GEORGE POLYA: HOW TO SOLVE IT

G. Polya,How to Solve It“, 2nd ed.,
Princeton University Press, 1957, ISBN 0-691-08097-6.

1 UNDERSTANDING THE PROBLEM
You have to understand the problem. What is the unknown? What are the data? What is the condition? Is it possible to satisfy the condition? Is the condition sufficient to determine the unknown? Or is it insufficient? Or redundant? Or contradictory? Draw a figure. Introduce suitable notation. Separate the various parts of the condition. Can you write them down?

2 DEVISING A PLAN
Find the connection between the data and the unknown. You may be obliged to consider auxiliary problems if an immediate connection cannot be found. You should obtain eventually a plan of the solution. Have you seen it before? Or have you seen the same problem in a slightly different form? Do you know a related problem? Do you know a theorem that could be useful? Look at the unknown! And try to think of a familiar problem having the same or a similar unknown. Here is a problem related to yours and solved before. Could you use it? Could you use its result? Could you use its method? Should you introduce some auxiliary element in order to make its use possible? Could you restate the problem? Could you restate it still differently? Go back to definitions. If you cannot solve the proposed problem try to solve first some related problem. Could you imagine a more accessible related problem? A more general problem? A more special problem? An analogous problem? Could you solve a part of the problem? Keep only a part of the condition, drop the other part; how far is the unknown then determined, how can it vary? Could you derive something useful from the data? Could you think of other data appropriate to determine the unknown? Could you change the unknown or data, or both if necessary, so that the new unknown and the new data are nearer to each other? Did you use all the data? Did you use the whole condition? Have you taken into account all essential notions involved in the problem?

3 CARRYING OUT THE PLAN
Carry out your plan. Carrying out your plan of the solution, check each step. Can you see clearly that the step is correct? Can you prove that it is correct?

4 LOOKING BACK
Examine the solution obtained. Can you check the result? Can you check the argument? Can you derive the solution differently? Can you see it at a glance? Can you use the result, or the method, for some other problem?

Another way of summarising the ideas in George Polya’s book “How to solve it”:

SEE , PLAN , DO , CHECK

Understand the Problem – (SEE)
Carefully read the problem.
Decide what you are trying to do.
Identify the important data.
Devise a plan – (PLAN)
Gather together all available information.
Consider some possible actions:
look for a pattern;
draw a sketch;
make an organised list;
simplify the problem;
quess and check;
make a table;
write a number sentence;
act out the problem;
identify a sub-task; and
check the validity of given information.
Carry out the plan – (DO)
Implement a particular plan of attack.
Revise and modify the plan as needed.
Create a new plan if necessary.
Check the answer – (CHECK)
Ensure you have used all the important information.
Decide whether or not the answer makes sense.
Check that all of the given conditions of the problem are met by the answer.
Put your answer in a complete sentence.

OBSERVATION: POLYA’S ideas about problem solving show a sequence of form, allowing one to observe, enhance, and define problems through the use of series, or progression. Do art, science, and mathematics have common ground for investigation? Is there a similarity between these three seemingly disparate fields of study? Posing a problem, recognizing its parameters, observing it, and ultimately solving it are essential to the function of curiosity and investigation, and are central to the process of creativity. HEURISTICS: involving or serving as an aid to learning, discovery, or problem-solving by experimental and especially trial-and-error methods, also: of or relating to exploratory problem-solving techniques that utilize self-educating techniques (as the evaluation of feedback) to improve performance such as a heuristic computer program.