ALGOSPHERE
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An
enterprise about suffering
INTRODUCTION TO
SCIENTIFIC ALGONOMY
This Algosphere project consists in producing, on this website and eventually as a book, a document that presents the first elements of a new discipline which is tentatively called scientific algonomy or algoscience. The term algonomy is explained elsewhere. Scientific algonomy may be defined as a branch of systematic knowledge where cumulative verifiable information on the whole range of theoretical and practical matters pertaining specifically to suffering, is sought, or used, in conformity with recognized scientific methods.
The following preliminary work is offered.
METHODOLOGY IN SCIENTIFIC ALGONOMY
Methodology is necessary to algoscience in order to develop formally its conceptual basis and its methods. The word methodology here refers to the rationale and the philosophical assumptions that underlie a particular discipline, and that determine how methods (specific principles, practices, procedures) are deployed and interpreted. There can be no detailed guide on how to create a new science, but algoscientists could probably draw many lessons from studies on how modern knowledge is pursued, or on how new fields are being developed (e.g. pain research, scientific study of consciousness, sociology of happiness...). For now, the main ideas that are proposed in algoscience methodology can be summed up as follows.
The nature of scientific algonomy is a matter for people to explore, to invent, and to agree upon. This discipline is originally conceived as a comprehensive, theoretical and practical, 'soft' science. It appears to be a very large discipline, given its specific object, the phenomenon of suffering, and given its field, the set of all things that may concern directly or indirectly that formal object. Every modern science, it should be noted, seems to be exceedingly large, or indefinitely expansible. At this time, embryonic algoscience can be handled by "general algoscientists", but eventually the discipline, like others, will probably have to be divided into a number of specialized parts.
Recognition from the scientific community will come to algoscience inasmuch as its "paradigm" helps to produce new theoretical and technical knowledge about suffering and its management. But prior to any demonstrative results, the following considerations may invite confidence in the new paradigm.
Scientific algonomy considers suffering
as
the "specific object" of a "comprehensive" discipline.
For
the first time, suffering is dealt with as a whole and
intrinsic concern. Until now, this concern has generally
been subordinated to other preoccupations in politics,
economy, society, religion, morals, philosophy, medicine,
psychology, neurology, etc., and advances about suffering
have mostly followed from our interest in health, knowledge,
love, welfare, security, etc. In algoscience, there is a
reversal of perspective : suffering is not only specifically
and extensively considered, but it is also the chief
concern to which other preoccupations are subordinated.
Suffering, in its own
specificity, is the matter of
algoscience : it is not as such the matter of neuroscience,
psychotherapy, social work, or medicine because such
disciplines are primarily concerned with aspects of
suffering that are specific not to suffering itself, but to
neuron and brain, or mind and behavior, or social problems,
or health and illness. Hopefully, a general science of
suffering will make possible what
others were unable to allow in the knowledge and
management of suffering.
Scientific algonomy considers suffering as
a conceptually defined phenomenon. Events or things in the
real world are particular and unique, and it is the role of
science to turn them into conceptually defined phenomena or
facts that are general and comparable to one another. As a
conceptually defined phenomenon, suffering is a kind of
abstraction comprising temporal, spatial, subjective or
other types of attributes, but devoid of particularities
such as a date, a place, a specific individual's presence or
any other contingent condition of manifestation. This
abstractive process makes scientific knowledge possible,
because it makes it "verifiable". It may be reminded that
there is no truth in science, but only theories that at all
time can be proved or disproved. In the same line of
thought, it may be noted that all matters that may concern
suffering can be treated in algoscience, but only inasmuch as
they are amenable to scientific verification : religious or
philosophical viewpoints on suffering, for example, belong
in some aspects to science, but in their specificity they
belong to another sphere.
Scientific algonomy considers suffering as
an empirical concept, because it is a psychological process
that can be observed through the behavior or the functioning
of groups, individuals, bodies, brains, neurons… Suffering
can be measured and modified, augmented or diminished,
started or stopped. Objective correlations can be
established, and empirical knowledge can be developed.
Scientific algonomy considers suffering with a radical, typically scientific stance of objectivity. It does not value suffering negatively nor positively. Consequently, parts of algoscience that are evaluative (e.g. critical studies of theories), or prescriptive (e.g. developmental studies of antalgic factors), or even factual (e.g. inventorial collections), are scientific only inasmuch as "statements of existence of value" are used rather than "intrinsic value judgments". Criteria must be made explicit, in particular, when suffering is said to be good or bad, useful or useless, acceptable or unacceptable, avoidable or unavoidable, light or severe, etc. Authors of algoscientific documents should mandatorily identify formally what, how, and especially "whose" values or interests are taken as parameters in their work. Neutral objectivity in science has often been a heuristic device, and hopefully it will have the same serendipity with suffering. Besides, there is a place for ethics in algoscience. Scientific algonomy cannot and should not have an ethical position, but students of suffering should have one! In short, algoscience as a discipline has only one purpose : universal knowledge about suffering. By itself, it has no other goal, value, strategy, or program of action.
There is presently no widely used definition of suffering. Generally, suffering refers to an unpleasant pychological or mental experience, while pain refers to an unpleasant physical or sensory experience. However, a purely mental distress is sometimes called a pain, and a purely physical hurt is sometimes called a suffering. This is so because both physical pain and mental suffering are unpleasant emotional or affective experiences, and because there is no unambiguous word to refer generically to this kind of experiences.
It is proposed here, for algoscience's purpose, to use the term suffering for referring to any unpleasant experience, and to distinguish when necessary between generic suffering, elementary suffering, physical suffering, mental suffering, and eventually other kinds of suffering.
Suffering, or generic suffering, is used as a term to refer to any affectively unpleasant experience.
Elementary suffering could be technically defined as the psychoneural process that constitutes the conscious subjective unpleasantness which can be found in any unpleasant emotional experience. Possible synonyms are unpleasantness, negative hedonic affect, algic affect.
Physical suffering is a synonym for the word pain as it is defined by the International Association for the Study of Pain : "Pain is an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage."
Mental suffering could be defined, similarly, as an upleasant mental and emotional experience associated with actual or potential psychological damage. Possible synonyms are distress, suffering (without adjective when the context clearly points to mental suffering), emotional suffering, psychological suffering. Among the main experiences that may be called mental sufferings, there are despair, anguish, anxiety, dismay, depression, sadness, sorrow, grief, malaise, discomfort, dissatisfaction, discontentment, disgust, aversion, exasperation, anger, rage, hatred, hostility, envy, jealousy, privation, frustration, heartbreak, inquietude, fear, terror, horror, shame, guilt, remorse, humiliation, boredom, tedium, alienation, affliction, unhappiness...
Measurement and estimation are of prime importance for most rational activities dealing with suffering, and quantitative studies concerning suffering should be developed as an independent subdiscipline, which could be called algometry. A few preparatory notes for algometry are given here.
Jeremy
Bentham (1748-1832) has prompted much thoughts, in ethical
philosophy and in political economy, with his calculus of
pleasures and pains. Bentham mentions seven circumstances
that affect the value of an actual or potential pleasure or
pain : 1- its intensity; 2- its duration; 3- its certainty
or uncertainty (how sure are we of its existence?) ; 4- its
propinquity (proximity) or remoteness (is it present or more
or less future?); 5- its fecundity (how much sensations of
the same kind does it necessarily bring about?); 6- its
purity (how much sensations of the opposite kind does it
necessarily bring about?); 7- its extent (how many people
are affected by it?). Modern utilitarians, in their
computations, sometimes use hedons and dolors as units for,
respectively, pleasures and pains.
The International Society for Panetics has inquired, since its foundation in 1991, into quantification
of matters related to the infliction of suffering (see
Quantification Research about Suffering at the ISP). Ralph Siu, the first theorist of panetics,
has proposed a unit, the dukkha, for measuring suffering as
a product of three factors : intensity, duration and number
of persons affected.
Pain
questionnaires of various kinds (some are quite long) are
being developed in medicine for appraising pain in patients.
The most usual and simple device is the 5 or 10-steps scale,
which serves to communicate the intensity degree of a pain,
and which can be numerical, verbal, or visual-analog. Pain
may be a purely subjective phenomenon, but its treatment has
to be objective; therefore, pain intensity is measured
according to "what the patient says", and thus the objective
behavioral data collected from what the patient expresses
become the basis of an objective pain measurement. Research
shows that this method is more reliable than any other for
assessing pain in patients. An important book in this area
is "Handbook of Pain assessment", by Melzack and Turk.
Suffering in
groups of individuals is sometimes tentatively quantified by
using social indicators (like the Poverty Index), statistics
on problems related to suffering (such as illnesses, deaths,
crimes, human rights violations...), questions addressed to
a sample of a population in a survey poll (like surveys
about happiness), indexes made up with various data (see the
idea of
The International Human Suffering Index), etc.
A lot
of micro or minor sufferings is endured by everybody each
day, and medium suffering can be quite frequent as well.
Dealing with that pervasive non major suffering in the same
framework as the major one is often practically unfeasible,
strategically counterproductive, and morally unacceptable.
Distinguishing between major and non major suffering is of
course a matter of qualitative appreciation or value
judgment, but it is clearly also a matter of applied
algometry.
In the
field of psychophysiological measurement, various equipments
(e.g. stimulus gauges, reflex gauges, nerve impulse
recorders, electroencephalograms, scanners) are used to
probe the measurable organic basis of physical pain or
psychological suffering. This field has a long history that
should be recapitulated as a part of algometrics. Some
important concepts are the dol (a unit of pain), the JND
(just noticeable difference), the Weber-Fechner law (the
amount of a perception is proportional to the natural
logarithm of the stimulus)… Generally, measurable aspects
that are most significant to algometry are intensity,
acuteness, dullness, aversion, duration, length, frequency,
recurrence… It may be noted that as a psychophysiological
phenomenon, suffering can be regarded under various aspects
relating to neurology, endocrinology, affectivity,
cognition, volition… Each aspects may require a special
algometric treatment.
Eventually, in order to have a clear view of suffering in
the world, an algometric epidemiology should be developed.
One of the uses of this specialty could be to provide a
periodical inventory of countable cases of major suffering
that can be identified at various scales (global, national,
local...) and in various areas (health care, social
services, economic security, legal system, etc.).
There
are still other aspects of suffering that need to be
measured : its consequences, causes, remedies, contextual
factors, costs, benefits, foreseeability, measurability,
diminishability, augmentability, and other economical,
social, ethical, political, strategical, or technical
aspects that can be relevant to its study or its management.
Four levels of measurement
were proposed by Stevens: nominal, ordinal, interval
or ratio measurement : see
Level of Measurement, in Wikipedia.
Also of interest is
Stevens' Power Law, a proposed relationship between the
magnitude of a physical stimulus and its perceived intensity
or strength, which is widely considered to supersede the
Weber-Fechner law.
From
A talk with Daniel Gilbert : "What does it take to study
something scientifically? One word: Measurement. If you can
measure something, you can study it scientifically. Can we
measure a person's subjective emotional experience? You bet.
People can tell you with both words and actions what they
are experiencing (...) and these reports are the essential
data on which the science of experience is built. (...)
optometry is another one of those sciences that is built
entirely on people's reports of subjective experience. The
one and only way for an optometrist to know what your visual
experience is like is to ask you, 'Does it look clearer like
this or (click click) like this?' On the basis of your
answers, the optometrist is able to create a lens that
corrects your vision quite precisely. Indeed, without your
report of your subjective visual experience, optometry would
be impossible. No 'objective test' — no eye test, no blood
test, and no brain test — can provide this information."
Finally, a thorough review of the literature about quantification and mathematization related to suffering should be a permanent feature of algometry.
Collecting and classifying are usually among the first activities that are done within a new discipline. It is necessary to collect facts, ideas, documents, and to classify them methodically for convenient retrieval and handling. In scientific algonomy, lists as exhaustive as possible should be set up concerning people or animals who suffer, kinds of suffering, causes of suffering, people and organizations who cause suffering, solutions or strategies relative to suffering, people and organizations who contribute to stop, diminish or prevent excessive suffering, documents having to do with suffering, and many other topics. See a page in preparation : Collecting and Classifying in Scientific Algonomy.
It is important in scientific algonomy to develop a bibliographic subspecialty dealing with documents that can be found on paper, or on the Internet, or on other media, and that are relevant to the knowledge and management of suffering. See a page in preparation : Bibliography in Scientific Algonomy.
Terminology here refers to the usage and study of terms and expressions used in scientific algonomy. See a page in preparation: Terminology in Scientific Algonomy.
FRENCH ABSTRACT — RÉSUMÉ EN FRANÇAIS
Introduction à l'algonomie
scientifique
Ce projet d'Algosphère consiste à
produire un document qui présente les premiers éléments d'une
nouvelle discipline appelée provisoirement algonomie
scientifique ou
algoscience.
L'algonomie scientifique peut se définir comme une branche du savoir
systématique où des connaissances vérifiables et cumulatives
concernant toute la variété des matières théoriques et pratiques qui
touchent spécifiquement à la souffrance, sont recherchées, et
utilisées, en conformité avec des méthodes scientifiques reconnues. La méthodologie
de la nouvelle discipline fait apparaître que l'étude
algoscientifique de la souffrance relève d'un nouveau paradigme
concernant cet objet, qui dès lors peut être considéré comme
spécifique, premier, empirique, et digne d'un traitement aussi objectif
et exhaustif que possible. Il est proposé d'utiliser le terme
souffrance pour désigner toute expérience affectivement désagréable
et de distinguer au besoin entre souffrance générique
(souffrance au sens général), souffrance élémentaire (le
désagréable au sens technique), souffrance physique
(douleur), et souffrance mentale. Quelques notes préparatoires
sont présentées concernant l'étude quantitative de la souffrance ou
algométrie. La collection (des faits, des idées, des
documents) et la classification en algonomie scientifique sont abordées en ce qui
concerne les sortes de souffrance, les gens ou les animaux qui
souffrent, les causes de souffrance, les gens et les organisations qui contribuent à produire la souffrance, les
solutions ou les stratégies relatives à la souffrance, les gens et
les organisations qui contribuent à arrêter, à diminuer ou à
prévenir la souffrance excessive, et d'autres sujets. Enfin, une page en préparation est présentée sur la bibliographie en
algoscience et une autre sur la terminologie.
© Algosphere, Montreal 2007
Last modification : 2007/11/14
Email : info@algosphere.org
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