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 | 6/21/02; 3:20:48 PM by SPH |
| Downloaded beta 0.7 of ActiveRenderer |
 | Will check out that story as class prep assignments allow. There seems to be a Mac System 9 problem with downloading. M. Barrot has passed the word to Evectors. |
 | Basic Foci |
| Family |
| Family History |
| The family history would reach back through lines that led to present generation of children (Daniel, Quinn, Madeleine, Hannah, Grace Ann). It would require some geneological work that might be eased by use of the instant outliner. |
| Ecology/Marine Ecology |
| Earth Trends |
 | Data Tables |
| Searchable Database |
| Country Profiles |
| The Way |
| Ecology is a unified organization of knowledge |
| Ecology is a unified organization of knowledge |
| Ecology seeks to establish the laws of nature |
| Ecology studies natural systems in their Gaian context |
| Ecology is holistic |
| Ecology is teleological |
| Ecology explains events in terms of their role with the spatio-temporal Gaian hierarchy |
| Fundamental knowledge is inherited |
| Fundamental knowledge is ineffable and we mainly have access to it by intuition |
| Ecological knowledge is built up by organizing knowledge in the mind |
| The mind contains a hierarchical organization of instructions and an associated model or dynamic map |
| Ecology is qualitative |
| Only qualitative vernacular models can provied the informational basis for adaptive behavior |
| Ecology is subjective |
| Man is cognitively adjusted to the environment in which he evolved |
| Ecology is emotional |
| Ecology is a faith |
| Ecology reflects the values of the Biosphere |
| A proposition can only be verified in terms of the paradigm or model of which it is a part. |
| The Biosphere is one |
| Gaia is a spatio-temporal entity |
| Gaia, seen as a total spatio-temporal process, is the unit of evolution |
| Stability rather than change is the basic feature of the living world |
| Gaia is alive |
| Natural systems are homeostatic |
| Natural systems are homeorhetic |
| The Gaian process is not random |
| Gaian processes are purposive |
| Life processes are dynamic |
| Life processes are creative |
| Life processes are anticipatory |
| Living things seek to understand their relationship with their environment |
| Living systems are intelligent |
| Consciousness is not a prerogative of man |
| Gaia is the source of all benefits |
| The Biosphere displays order |
| Gaian order is critical |
| There is no fundamental barrier separating man and other living things |
| The Biosphere is a a hierarchical organization of natural systems |
| Competition is a secondary Gaian interrelationship |
| Cooperation is the primary Gaian interrelationship |
| When Gaian control breaks down, behavior becomes heterotelic |
| Natural systems can only behave homeotelically within their 'tolerance range' |
| Living things can only behave homeotelically within their field |
| A system's field or its ordered environment is provided by the heirarchy of larger systems of which it is a part |
| As the environment diverges from the optimum, biological maladjustment increases |
| As the environment diverges from the optimum, social maladjustment increases |
| As the environment diverges from the optimum, cognitive maladjustment increases |
| Man is psychically maladjusted to the world depicted by the paradigm of science |
| The internalization of control increases stability |
| Life proccesses are sequential and tend towards the most stable state |
| Increased complexity leads to greater stability |
| By increasing its diversity a system increases the range of encironmental challenges to [with?] which it is capable of dealing |
| Natural systems are hometelic to Gaia |
| In a vernacular society, education is homeotelic to Gaia |
| In a vernacular society, settlements are homeotelic to Gaia |
| In a vernacular society economic activity is homeotelic to Gaia |
| In a vernacular society technology is homeotelic to Gaia |
| In an ecological economy, money is homeotelic to Gaia |
| The vernacular communicty is largely self-sufficient |
| The vernacular community is the unit of homeotelic behavior |
| Vernacular man follows the Way |
| For vernacular man, to increase his stock of 'vital force' is to follow the Way |
| For vernacula man, to serve his gods is to follow the Way |
| Progress is enti-evolutionary and is anti-Way |
| To keep to the Way, society must be able to correct any divergence from it |
| The Great Reinterpretation requires a conversion to the world-view of ecology |
| A1:Does the entropy law apply to the real world? |
| A2: What is information? |
| A3: The artificialistic fallacy |
| A4: The need for a feedback mechanism linking behavior to evolution |
| MRC |
| MPA resources |
| Marine Estuarine Environments--Conservation of Biodiversity |
| Project Description |
| CEC : Conservation of Biodiversity - Project Details; Project Contacts; Partners; Publications and Documents; Related Publications. Cooperation on the Protection of Marine and Coastal Ecosystems. ... |
| CEC : Contracts, Jobs, RFPs - Positions available; Requests for proposals (RFP); Procurement policy. Home | Latest News | Calendar ... |
| CEC : Citizen Submissions on Enforcement Matters - List of submissions. ... |
| MPA of US |
| Google's items related to this... |
| Marine Protected Areas - April Update Each case study in the What is a Marine Protected Area section is complemented by a narrated slide show. ... |
| National Marine Sanctuaries - |
| Gulf of Maine Council - Position Announcements Contact Us. People Finder. Discussion Forum. Calendar of Events. Awards. Habitat Restoration Grants. ... |
| COMPASS Online - |
| - NMFS Press Release on FW33 Lawsuit Remedy and Supporting Documents. Overview: Introduction to the Federal Fishery Management Process; Structure of the New England ... |
| Ocean and Coastal Resource Management - Welcome to the Office of Ocean and Coastal Resource Management. Welcome to the Office of Ocean and Coastal Resource Management. ... |
| National Estuarine Research Reserves - National Estuarine Research Reserves. ... The National Estuarine Research Reserve System protects ... |
| Fully-protected marine reserves - [>], Introduction Worldwide fisheries are in trouble, and habitats and species are being lost ... |
| Stellwagen Bank National Marine Sanctuary - ... WELCOME to the Stellwagen Bank Sanctuary Web Page. The Gerry E. Studds-Stellwagen Bank National ... |
| NCEAS - |
| System |
| General Systems Theory |
| General References |
| Joslyn Turchin Heylighen's Principia Cybernetica Web |
| History of Systems |
| ISSS History/Review |
| Evolution of Systems Theory |
| Bella Banathy's Paper for ISSS |
| System Theory ala Miller |
| 5/8/02; 7:49:28 PM by SPH |
| Bryan S. Coffman's Introduction |
| As relates to Gaia - a joint presentation in '92 JG and JL Miller |
| Chapter 4 - ... http :// www . newciv . org / ISSS_Primer / asem05jm . html ). It was generally expected that ... es/sociocybernetics/indice.html; Autopoiesis Related Web Sites at http://server ... |
| David Clark for his great Graphic Summary of the Structural side of Miller's Living System Theory |
| The outline of Living System Thoughts (Structure and Process) |
| SYSTEM-RELATED HYPOTHESES |
| 1. STRUCTURE (from David Clark's Intro-- see above) |
| These are liberally and literally quoted from ME3110 - at Systems Realization Laborartory. Created by David D. Clark, (srl.marc.gatech.edu) |
| Matter-Energy Subsystems |
| Supporter |
| The Supporter subsystem is the subsystem which maintains the proper spacial relationships among components of the system, so they can interact without weighting each other down or crowding each other. |
| An example of a supporter in a living system is bone. |
| An example of a supporter in an artifact is a rivet. |
| The supporter can be divided into three classes: Solids, Liquids and Gasses, Configurations of Matter, and Fasteners, Joints and Attachments. |
| Solids, Liquids and Gasses |
| * suspended within liquids / gases, floats |
| * mechanical ground |
| * lubricants |
| Configurations of Matter |
| * masses, platforms, plates, pallets, decks, grating |
| * bases, pads, mounts, ramps |
| * magnetic suspension |
| * frame, skeleton, body |
| * tower, pillar, column, beam |
| * stake, brace, boom, bone, hub |
| * hanger, crane, harness, chain, cable, slings, straps, ties |
| * legs, arms, stands, walls, chocks |
| * "Boundary-Barrier" concepts (e.g., casing) |
| Fasteners, Joints and Attachments |
| * nails, screws, bolts, nuts, washers, snap fits |
| * welds, rivets, brackets, couplers |
| * ties, clips, clamps, collars, vise |
| * adhesives, epoxies, tape, glue, solder, suction cup |
| * spacers, bearings, joints, hook & loop fasteners |
| * claw, hook, scoop, anchor, magnet |
| Ingestor |
| The Ingestor subsystem is the subsystem which brings matter-energy across the system boundary from the environment. |
| An example of an ingestor in a living system is a mouth. |
| An example of an ingestor in an artifact is an intake hopper. |
| The ingestor can be divided into two classes: Orifices and Input Receptacles. |
| Orifices |
| * orifices: mouth, hole, doorway, opening, inlet |
| * "Distributor" concepts |
| Input Receptacles |
| * hopper, chute, funnel, cart |
| * electrical receptacles: plugs, outlets, contacts |
| * "Boundary-Filter" concepts |
| * "Matter-Energy Storage" concepts |
| Distributor |
| The Distributor subsystem is the subsystem which carries inputs from outside the system or outputs from its subsystems around the system to each component. |
| An example of a distributor in a living system is the circulatory system. |
| An example of a distributor in an artifact is a conveyor belt. |
| The distributor can be divided into two classes: Matter Distributors and Energy Distributors. |
| Matter Distributors |
| * hose, tube, pipe, conduit, duct, fittings/couplers |
| * rail, track, groove, slot |
| * ditch, canal, channel, tunnel, bridge, span, aisle, walkway, road |
| * rope, cable, cord, chain |
| * truck, railroad, plane, convoy, airlift, car |
| * automated production line, conveyor system, escalator, elevator |
| * mixer, blender, diffuser, brush, pressure roller |
| Energy Distributors |
| * wire, power cord, jumper, cable, breadboard / electrical bus, terminal |
| * baffle, reflector, lens train |
| * gears, sprocket & chain, pulley & rope, sheaves & belt |
| * diffusion through space and mass/matter |
| * shaft, axle, rod, linkage |
| * mechanical joints |
| * ratchet mechanism |
| Converter |
| The Converter subsystem is the subsystem which changes inputs to the system into forms more useful for the special processes of that particular system. |
| The converter and the producer subsystems can be easily confused. The definition for the producer: |
| The Producer subsystem forms stable associations that endure for significant periods among matter-energy inputs to the system or outputs from its converter, the materials syntehsized being for its growth, damage repair, or replacement of components of the system, or for providing energy for moving or constituting the system's outputs of products or information markers to its suprasystem. |
| Scott Cowan has clarified these definitions as they relate to mechanical systems: |
| Converter, the subsystem which changes matter-energy within the system into more useful forms to be utilized elsewhere (for other purposes) within that particular system. The change of matter-energy is characterized as relatively easy to reverse (neglecting losses). These changes generally include phase changes of matter (e.g., solid to liquid), force transformations (e.g., rotational to linear), and conversion between energy types (chemical to electrical). Nonliving system examples include heaters, coolers, linkages, cams, thermocouples, and elastically-deformable materials. |
| Producer, the subsystem which processes and changes matter-energy in a permanent or relatively irreversible manner. The new matter-energy is then used for development of some aspect of the system, or for providing energy to aid in the development of the system's product(s). These functions may include system "growth," "damage repair," "replacement", and moving the system's products. Within nonliving systems, the producer is not necessarily something tangible, such as a component at this level. Instead, the producer is generally abstract and is embodied within a process or interaction (as opposed to a product or artifact). These processes generally include permanent shape changes and constituent material changes within matter (e.g., plastic deformation), as well as assemblies of matter. Nonliving system examples include building, manufacturing, and assembly processes, machining processes, relatively irreversible chemical reactions, and heat transfer. |
| An example of a converter in a living system is the stomach. |
| An example of a converter in an artifact is an AC to DC rectifier. |
| The converter can be divided into three classes: Conversion of Matter, Conversion of Forces and Conversion of Energy. |
| Conversion of Matter |
| Phase changes: pressure, temperature, composition |
| * heater, boiler, cooler, heat exchanger |
| * compressor, nozzle, piston, plunger |
| * dryer, dehumidifier, condenser |
| Conversion of Forces |
| * Mechanisms: cam, linkage, gear train, sprocket & chain system, sheaves, belt-pulley system, rope-pulley system, hydraulics, pneumatics |
| * Wheels: trolleys, trucks, rollers, balls, casters, wheels |
| * wing, blade, impeller, propeller, pinwheel |
| * electrical transformers, electrical rectifiers, electrical adapters, amplifiers |
| * mechanical joints, wrench, lever, crank arm, scotch yoke |
| Conversion of Energy |
| * resistor, brakes, "friction"-based devices |
| * chemical reactions, enzymes |
| * piezo-electric materials, diaphragm, elastic deformation of materials |
| * thermocouple, solar cell |
| * nuclear reactor processes |
| * windmill, waterwheel |
| * "motor / electromechanical"-based devices |
| Producer |
| The Producer subsystem forms stable associations that endure for significant periods among matter-energy inputs to the system or outputs from its converter, the materials syntehsized being for its growth, damage repair, or replacement of components of the system, or for providing energy for moving or constituting the system's outputs of products or information markers to its suprasystem. |
| The producer and the converter subsystems can be easily confused. The definition for the converter: |
| The Converter subsystem is the subsystem which changes inputs to the system into forms more useful for the special processes of that particular system. |
| Scott Cowan has clarified these definitions as they relate to mechanical systems: |
| Producer, the subsystem which processes and changes matter-energy in a permanent or relatively irreversible manner. The new matter-energy is then used for development of some aspect of the system, or for providing energy to aid in the development of the system's product(s). These functions may include system "growth," "damage repair," "replacement", and moving the system's products. Within nonliving systems, the producer is not necessarily something tangible, such as a component at this level. Instead, the producer is generally abstract and is embodied within a process or interaction (as opposed to a product or artifact). These processes generally include permanent shape changes and constituent material changes within matter (e.g., plastic deformation), as well as assemblies of matter. Nonliving system examples include building, manufacturing, and assembly processes, machining processes, relatively irreversible chemical reactions, and heat transfer. |
| Converter, the subsystem which changes matter-energy within the system into more useful forms to be utilized elsewhere (for other purposes) within that particular system. The change of matter-energy is characterized as relatively easy to reverse (neglecting losses). These changes generally include phase changes of matter (e.g., solid to liquid), force transformations (e.g., rotational to linear), and conversion between energy types (chemical to electrical). Nonliving system examples include heaters, coolers, linkages, cams, thermocouples, and elastically-deformable materials. |
| An example of a producer in a living system is the adrenal gland. |
| An example of a producer in an artifact is a battery charger. |
| The producer can be divided into two classes: Product Formation and Matter-Energy Alterations. |
| Product Formation |
| * manufacturing processes |
| * assembly processes |
| * building processes |
| Matter-Energy Alterations |
| * chemical reactions |
| * machining processes (altering aspects of shape): cutting, rolling, grinding, drawing, abrasive applications, plastic deformation |
| * energy transfer and conversion (e.g., heat exchange) |
| Matter-Energy Storage |
| The Matter-Energy Storage subsystem is the subsystem which places matter or energy at some location in the system, retains it over time, and retrieves it. |
| An example of a matter-energy store in a living system is fatty tissue. |
| An example of a matter-energy store in an artifact is a watch spring. |
| The matter-energy store can be divided into two classes: Containers and Potential Energy Storage. |
| Containers |
| Containers are used to hold solids, liquids or gasses for later use within the system. They can be divded into two sub-categories: containers for solids and containers for liquids and gasses |
| Potential Energy Storage |
| Energy can be stored in the system as a potential. This potential energy can take many forms: chemical, electrical, heat, deformation or motion (as a controlled kinetic energy), for example. |
| * living sysems: fatty tissue |
| * electricity: battery, capacitor, inductor |
| * elastic materials: springs, rubber bands, elastic deformation |
| * insulated mass, heated mass |
| * height difference |
| * compressed liquid or gas |
| * repetitive motion: flywheel, pendulum, vibratory system |
| Extruder |
| The Extruder subsystem is the subsystem which brings matter-energy across the system boundary from the environment. |
| An example of an extruder in a living system is a mouth. |
| An example of an extruder in an artifact is an intake hopper. |
| The extruder can be divided into two classes: Orifices and Input Receptacles. |
| Orifices |
| * orifices: mouth, hole, doorway, opening, inlet |
| * "Distributor" concepts |
| Input Receptacles |
| * hopper, chute, funnel, cart |
| * electrical receptacles: plugs, outlets, contacts |
| * "Boundary-Filter" concepts |
| * "Matter-Energy Storage" concepts |
| Motor |
| The Motor subsystem is the subsystem which moves the system or parts of it in relation to part or all of its environment or moves components of its environment in relation to each other. |
| An example of a motor in a living system is a skeletal muscle. |
| An example of a motor in an artifact is a DC motor. |
| The motor can be divided into four classes: Mechanical Devices, Material Properties, Gravity and Muscle. |
| Mechanical Devices |
| Compress, pressurize, produce current, torque, etc. |
| * DC/AC motor, generator, actuator |
| * pump, fan, vacuum, blower, impeller |
| * compressor |
| * engine, turbine |
| Material Properties |
| * elasticity (springs) |
| * thermal (expansion, contraction, phase changes) |
| * magnetism (attraction, repulsion) |
| * chemical properties (combustion, rocket engines) |
| * density (e.g., buoyancy) |
| Gravity |
| Muscle |
| Information Subsystems |
| Timer |
| The Timer subsystem is the subsystem which transmits to the decider information about time-related states of the environment or of components of the system. This information signals the decider of the system or deciders of subsystems to start, stop, alter the rate, or advance or delay the phase of one or more of the system's processes, thus coordinating them in time. |
| An example of a timer in a living system is the vagus nerve, which controls the heart's rhythm. |
| An example of a timer in an artifact is a fuse. |
| The timer can be divided into three categories: Fixed Interval Timers, Flexible Interval Timers, and Biological Timers. |
| Output Transducer |
| The Output Transducer subsystem is the subsystem which puts out markers bearing information from the organism, changing markers within the organism into other matter-energy forms which can be transmitted over channels in the organism's environment. |
| An example of an output transducer in a living system are the vocal cords. |
| An example of an output transducer in an artifact is a warning light. |
| The output transducer can be divided into three categories: Output Interfaces, Indicators, and Transmitters |
| Encoder |
| The Encoder subsystem is the subsystem which alters the code of information input to it from other information processing subsystems, from a "private" code used internally by the organism into a "public" code which can be interpreted by other organisms in its environment. |
| An example of an encoder in a living system is the brain's language center. |
| An example of an encoder in an artifact is a 7-segment LED encoder. |
| The encoder has only one class: Encoding Devices. |
| Encoding Devices |
| * translator, interpreter |
| * cryptographer, programmer |
| * thesaurus, signal guide, dictionary |
| * coding machine, cryptography algorythm, 7-segment LED encoder |
| * meterologist, consultant |
| * teletypewriter, computer, printer |
| * disk drive, tape drive, CD-writer |
| * record player |
| * writer, painter, musician |
| * Living Systems: language center in the brain |
| Decider |
| The Decider subsystem is the executive subsystem which receives information inputs from all other subsystems and transmits to them information inputs that control the entire organism. |
| An example of a decider in a living system is the brain's cerebral cortex. |
| An example of a decider in an artifact is a computer program. |
| The decider has only one class: Controllers and Processors. |
| Controllers and Processors |
| * microprocessor (e.g., CPU) |
| * controller (e.g., PLC, CNC, NC, AC) |
| * manual control (human intervention) |
| * computer program |
| * calculator, computer |
| * thermostat |
| * feedback controllers |
| * Living Systems: cerebral cortex |
| * Living Systems: natural and biological "programs" (instincts, mating rituals, territorial displays) |
| Memory |
| The Memory subsystem is the subsystem which carries out the second stage of the learning process, storing various sorts of information in the organism for different periods of time. |
| This system is not present in fungi or plants. |
| An example of a memory in a living system is the brain. |
| An example of a memory in an artifact is a tape backup system. |
| The decoder can be divided into two classes: Electronic Memory and Other Memory Devices. |
| Electronic Memory |
| * Read/Write Memory: RAM, magnetic media (video or cassette tape, floppy disk) |
| * Read Only Memory: ROM (CD-ROM, EPROM) |
| Other Memory Devices |
| * monument, library, book, journal, bank |
| * file, letter, meeting minutes, picture |
| * recordings |
| * bulletin board |
| * Living Systems: Brain |
| Associator |
| The Associator subsystem is the subsystem which carries out the first stage of the learning process, forming enduring associations among items of information in the system. |
| This system is not present in fungi or plants. |
| An example of an associator in a living system is the human brain's frontal lobe. |
| An example of an associator in an artifact is a neural network. |
| The associator has only one class: Associator Devices. |
| Associator Devices |
| * computer, computer program |
| * logic gates |
| * neural network |
| * Living Systems: frontal lobe in human brain |
| Decoder |
| The Decoder subsystem is the subsystem which alters the code of information input to it through the input transducer or internal transducer into a "private" code that can be used internally by the system. |
| An example of a decoder in a living system is the brain's visual center. |
| An example of a decoder in an artifact is a logical AND gate. |
| The decoder has only one class: Decoding Devices. |
| Decoding Devices |
| * translator, interpreter |
| * cryptographer, programmer |
| * thesaurus, signal guide, dictionary |
| * coding machine, encryption algorythm |
| * meteorologist, consultant |
| * teletypewriter, print reader, computer, close caption decoder |
| * pattern recognition devices, neural networks |
| * film camera |
| * electronic data processing systems: |
| o magnetic character / check reader |
| o laser barcode scanner |
| o punch card reader |
| o disk drive, tape drive, CD reader |
| o digital camera, video camera |
| * Living Systems: visual center in the brain |
| Channel and Net |
| The Channel and Net subsystem is the subsystem composed of a single route in physical space, or multiple interconnected routes, over which markers bearing information are transmitted to all parts of the system. |
| An example of a channel and net in a living system is a neuron. |
| An example of a channel and net in an artifact is a wire. |
| The channel and net has only one class: Channels and Nets. |
| Channels and Nets |
| * membrane, cytoplasm, nervous system, neuron |
| * memos, letters, postal system, email, the internet, telephones, pagers |
| * television, radio, newspapers |
| * wires, cables |
| * sound waves, radio waves |
| * optical coupling, fiberoptic fibers, light tubes |
| Internal Transducer |
| The Internal Transducer subsystem is the sensory subsystem which receives, from subsystems or components within the system, markers bearing information about significant alterations in those subsystems or components, changing them to other matter-energy forms of a sort which can be transmitted within it. |
| An example of an internal transducer in a living system is an enzyme. |
| An example of an internal transducer in an artifact is an automobile computer. |
| The internal transducer can be divided into two categories: Sensors and Other Internal Transducers. |
| Note that most items that are Input Transducers at one level of hierarchy may be Internal Transducers at the next higher level of hierarchy. For example, a sensor that detects a closing gate may be an input transmitter for the system that must react to the gate but for the system that includes the gate it is an internal transducer. |
| Sensors |
| Receive unformatted information from within the system. |
| * infrared, ultrasonic, laser, piezoelectric, electric eye, X-ray sensors |
| * motion, sound, light, radioactivity, etc. |
| * radar system, diaphragm mechanism |
| Other Internal Transducers |
| * suggestion box, time clock |
| * Living Systems: enzymes, pain receptors |
| Input Transducer |
| The Input Transducer subsystem is the sensory subsystem which brings markers bearing information into the system, changing them to other matter-energy forms suitable for transmission within it. |
| An example of an input transducer in a living system is an eyeball. |
| An example of an input transducer in an artifact is a keyboard. |
| The input transducer can be divided into three categories: Input Interfaces, Sensors, and Receivers. |
| Input Interfaces |
| Accept abstract, formatted data directly from outside sources. |
| * keyboard, mouse, scanner, serial & parallel devices |
| * switches, dials, knobs, control panels |
| * signal / function generator |
| * "Decoder" concepts |
| Sensors |
| Receive unformatted information directly from outside sources. |
| * infrared, ultrasonic, laser, piezoelectric, electric eye, X-ray sensors |
| * motion, sound, light, radioactivity, etc. |
| * radar system, diaphragm mechanism |
| Receivers |
| Receive information from outside sources. |
| * telephone, television, radio |
| * lens, magnifying glass |
| * microscope, telescope, binoculars, glasses |
| * hearing aid, photoelectric cell |
| * ear, eye, nose, tongue, skin pressure, skin temperature receptors |
| * lookout, antenna, microphone, sonarphone |
| * "Channel and Net" concepts |
| Matter-Energy and Information Subsytem(s) |
| Reproducer |
| The subsystem which is capable of giving rise to other systems similar to the one it is in. |
| The Reproducer subsystem is the subsystem which is capable of giving rise to other systems similar to the one it is in. |
| An example of a reproducer in a living system is the reproductive system of an organism. |
| An example of a reproducer in an artifact is a computer virus. |
| The boundary can be divided into three classes: Biological Reproduction, Chartering and Manufacturing or Supporting Artifacts. |
| Biological Reproduction |
| * reproductive system |
| * cell reproducers |
| * seeds |
| * cloning |
| Chartering (Reproduction through writing) |
| * computer programs (e.g., viruses) |
| * spin-off companies |
| * political revolutions & secessions |
| Manufacturing / Supporting Artifacts |
| * incubator |
| * copying machine |
| * scanner |
| * audio recording devices |
| * video recording devices (e.g., cameras) |
| * key duplicating machines |
| * casts, molds |
| * design & manufacturing centers |
| Boundary |
| The Boundary subsystem is the border between the system and the world, or between subsystems within a system. Its purpose is to hold the components together; to protect them from environmental stresses; and to exclude or permit entry to various sorts of matter-energy and information. |
| An example of a boundary in a living system is the skin of an organism. |
| An example of a boundary in an artifact is a storage case. |
| The boundary can be divided into two classes: Barriers and Filters. |
| Barriers |
| * membranes, cell walls, capsules, skin, fur, scales, feathers, hair, exoskeletons |
| * fences, gates, doors, walls, partitions, buildings |
| * bumpers, guard rails or posts, curbs |
| * armor, helmets |
| * boxes, bottles, casings, shells, enclosures, housing, conduits, coverplates, cartridges |
| * gaskets, rings, caulk, sealants, plugs |
| * insulation, coatings, finishes, paints, varnishes |
| Filters |
| * osmotic membranes, filters, screens, strainers |
| * fuses, surge protectors, resistors |
| * switches, relays, breakers, contacts, solenoids |
| * valves, vortex breakers |
| * shutters, blinds, vents |
| * locks (and keys), handles |
| 2. PROCESS |
| HYPOTHESIS 2-1: System components incapable of associating, or lacing experience which has formed such associations, must function according to rigid programming or highly standardized operating rules. It follows that as turnover of components rises above the rate at which the components can develop the associations necessary for operation, rigidity of programming increases. (H) |
| HYPOTHESIS 2-2: The more rapid reassignment of function from one component to another a long-surviving system has, the more likely are the components to be totipotential than partipotential. (M) |
| HYPOTHESIS 2-3: The more isolated a system is, the more totipotential it must be. (H) |
| HYPOTHESIS 2-4: A system's processes are affected more by its suprasystem that by its suprasuprasytem or above, and by its subsystems than its subsubsystems or below. (L) |
| 3. SUBSYSTEMS |
| 3.1 Subsystems Which Process Both Matter-Energy and Information |
| 3.1.2 Boundary |
| 3.1.2.2 Process |
| Matter-Energy Boundary. |
| HYPOTHESIS 3.1.2.2-1: When the boundary (except those portions containing the openings for the ingestor or the portions or the extruder) of one living system, A, is crossed by another, smaller living or nonliving system, B, of significant size, i.e., no smaller than the subsystems or subcomponents of A, more work must be expended than when B is transmitted over the same distance in space immediately inside or outside the boundary of A. (L) |
| Information Boundary. |
| HYPOTHESIS 3.1.2.2-2: More work must be expended in moving the marker bearing an information transmission over the boundary of a system at the input transducer than in making such a transmission over the same distance in the suprasystem immediately outside the boundary or in the system immediately inside it. (L) |
| HYPOTHESIS 3.1.2.2-3: The amount of information transmitted between points within a system is significantly larger than the amount transmitted across its boundary. (M) |
| HYPOTHESIS 3.1.2.2-4: The larger a system is and the more components it has, the larger is the ratio of the amount of information transmitted between points within the system to the amount of information transmitted across its boundary. (M) |
| 3.2 Subsystems Which Process Matter-Energy. |
| HYPOTHESIS 3/2-1: An optimal mean temperature at which process is most efficient is maintained by a living system. (L) |
| 3.2.2 Distributor |
| 3.2.2.1 Structure |
| HYPOTHESIS 3.2.2.1-1: The hierarchical structure of the distributor is arranged so that there is a geometrical progression from the sized of the region of the total system served by an average unit of its lowest echelon to the size of the region served by an average unit of its highest echelon. (M) |
| 3.2.2.2 Process |
| HYPOTHESIS 3.2.2.2-1: The farther a specific matter-energy transmission passes along a distributor from the point of its input to it and toward the final point of its from it, the more it is altered by lowering the concentration of the kinds of matter-energy it contains which are used by the system's subsystems and by increasing the concentration of the products or wastes produced by it and output by those subsystems. (H) |
| HYPOTHESIS 3.2.2.2-2: In general, total entropy per unit cubic contents increases progressively along a distributor between the points of input and output. (L) |
| 3.2.5 Matter-Energy Storage |
| 3.2.5.2 Process |
| HYPOTHESIS 3.2.5.2-1: If process A applied to any form of matter-energy always precedes process B (as, for example, converting precedes producing), variations imposed on the rate of process B by variations in the rate of process A can be decreased by storing a supply (or "buffer inventory") of the outputs from process A between the components which carry out the two processes. (H) |
| 3.3 Subsystems Which Process Information |
| HYPOTHESIS 3.3-1: Up to a maximum higher than yet obtained in any living system but less than 100 percent, the larger the percentage of all matter-energy input that it consumes in information processing controlling its various system processes, as opposed to matter-energy processing, the more likely the system is to survive. (M) |
| 3.3.1 Input Transducer |
| 3.3.1.2 Process |
| HYPOTHESIS 3.3.1.2-1: The intensity output signal of an input transducer varies as a power function of the intensity of its input, the form of the power function being Y= k (F-Fo) n, where Y is the intensity of the output signal, 0 is the physical magnitude of the input energies, Fo is a constant, the physical magnitude of the minimum detectable or threshold input energies, k depends on the choice of measurement units, and the exponent n varies with different modalities of the transducer. (M) |
| HYPOTHESIS 3.3.1.2-2: Living systems divide the intensities of information inputs into about seven categories, plus or minus two. |
| 3.3.3 Channel and Net |
| 3.3.3.1 Structure |
| HYPOTHESIS 3.3.3.1-1: The structures of the communication networks of living systems at various levels are so comparable that they can be described by similar mathematical models of nonrandom nets. (L) |
| 3.3.3.2 Process |
| HYPOTHESIS 3.3.3.2-1: In all channels c=w log2 (1 + P/N). That is, the maximum capacity (in bits per s) of a channel is equal to its bandwidth times the logarithm of (1 plus the ratio of the power of the signal to the power of the white Gaussian noise in the channel). (L) |
| HYPOTHESIS 3.3.3.2-2: There is always a constant systematic distortion between input and output of information in a channel. (H) |
| HYPOTHESIS 3.3.3.2-3: In a channel there is always a progressive degradation of information and decrease in negative entropy or increase in noise or entropy. The output information per unit time is always less than it was at the input. (H) |
| HYPOTHESIS 3.3.3.2-4: A system never completely compensates for the distortion in information flow in its channels. (L) |
| HYPOTHESIS 3.3.3.2-5: Strains, errors, and distortions increase in a system as the number of channels over which information transmission is blocked increases. (M) |
| HYPOTHESIS 3.3.3.2-6: A system tends to distort information in a direction to make it more likely to elicit rewards or less likely to elicit punishments to itself. (L) |
| HYPOTHESIS 3.3.3.2-7: The farther away along channels a component is from a process, or the more components there are between them, the more error there is in its information about that process. (L) |
| HYPOTHESIS 3.3.3.2-8: In general, the farther components of a system are from one another and the longer the channels between them are, the less is the rate of information flow among them. (M) |
| HYPOTHESIS 3.3.3.2-9: Use of multiple parallel channels to carry identical information, which farther along in the net can be compared for accuracy, is commoner in more essential components of a system than in less essential ones. (L) |
| HYPOTHESIS 3.3.3.2-10: The probability of breakdown of adjustment processes among subsystems of a system decreases as the number of parallel information channels serving it increases. (M) |
| HYPOTHESIS 3.3.3.2-11: The probability of error in or overload of an information channel is a monotonic increasing function of the number of components in it. (H) |
| HYPOTHESIS 3.3.3.2-12: Two-way channels which permit feedback improve performance by facilitating processes that reduce error. (M) |
| HYPOTHESIS 3.3.3.2-13: The greater the channeling of information processing, limiting the number of components to which a given item of information goes, the more do components of a system differ in how they decode and decide. (L) |
| HYPOTHESIS 3.3.3.2-14: If components of a system are closely connected spatially, have similar functions, or are made up of similar units, they are more alike in decoding and deciding than if they are remote or unlike. That is because interaction among units (for whatever reasons) tends to increase sharing of informations (L) |
| HYPOTHESIS 3.3.3.2-15: The functional segregation of components means that each one receives some information which the others do not. The greater this segregation of information, the more do the components differ in decoding and deciding. (L) |
| HYPOTHESIS 3.3.3.2-16: The less decoding and encoding a channel requires, the more it is used. (L) |
| HYPOTHESIS 3.3.3.2-17: When a channel has conveyed one signal or message, its use to convey others is more probable. (L) |
| HYPOTHESIS 3.3.3.2-18: Some information inputs of energic intensity above the threshold of an input transducer can affect behavior mediated by lower echelons of the system without affecting higher echelons. (M) |
| HYPOTHESIS 3.3.3.2-19: The information input with the greatest intensity or greatest signal-to-noise ratio is given priority processing, i.e., attention. (L) |
| HYPOTHESIS 3.3.3.2-20: A system gives priority processing to information which will relieve a strain (i.e., which it "needs"), neglecting neutral information. It positively rejects information which will increase a strain. (M) |
| HYPOTHESIS 3.3.3.2-21: In periods of stress and/or change in a system, the amount of information processing relevant to both task performance and adjustments among subsystems increases. (M) |
| 3.3.4 Decoder |
| 3.3.4.2 Process |
| HYPOTHESIS 3.3.4.2-1: As a system matures, it uses increasingly efficient codes, e.g., codes which require fewer binary digits or equivalent signals per input signal. These codes approach but never actually reach the theoretical minimum number of symbols required to transmit the information. Efficient codes also have the following characteristics: |
| (a) Simple symbols are used for the most frequent messages and more complex ones for the less frequent ones. |
| (b) The symbols are selected to minimize confusion among them. |
| (c) The symbols are chunked in long rather than short blocks. |
| (d) Limitations on the transmitter of the signal are taken into account. For example, if it transmit highly redundant signals, each one is not coded, but some of the redundancy is removed. |
| (e) Limitations on the receiver are taken into account. For example, distinctions to which the receiver cannot react are neglected. (L) |
| HYPOTHESIS 3.3.4.2-2: If a transmitter of information is putting out information coded to have H bits per symbol, and a noiseless channel has a capacity (bits per s) of C, then the channel cannot transmit at a rate faster than C/H symbols per s, though it is possible to encode the message so as to transmit at a rate of C/H-e symbols per s, where e is a positive fraction less than one and usually small, of C. (L) |
| HYPOTHESIS 3.3.4.2-3: The quantity e (see Hypothesis 3.3.4.2-2) decreases as a system matures and associates, gaining practice in coding information. (L) |
| HYPOTHESIS 3.3.4.2-4: If a transmitter with an information transmission rate (in bits per s ) of R is transmitting over a noisy channel-- and all living channels are noisy-- with a capacity (in bits per s) of C, and if R is less than C, there is a code which can make the transmission almost free of errors; and as the system matures and associates, gaining practice, it gradually approaches such transmission. (L) |
| |
| HYPOTHESIS 3.3.4.2-6: As the noise in a channel increases, a system encodes with increasing redundancy in order to reduce error in the transmission. (M) |
| HYPOTHESIS 3.3.4.2-7: If messages are so coded that they are transmitted twice, errors can be detected by comparing every part of the first message with every part of the second, but which of the tow alternative transmissions is correct cannot be determined. If they are transmitted three times, they can be both detected and corrected, by accepting the alternative on which two of the three transmissions agree. (M) |
| HYPOTHESIS 3.3.4.2-8: Over time a system tends to decrease the amount of recoding necessary within it, by developing more and more common systemwide codes. (L) |
| HYPOTHESIS 3.3.4.2-9: As the amount of information in an input decreases (i.e., as it becomes more ambiguous), the input will more and more tend to be interpreted (or decoded) as required to reduce strains within the system. (L) |
| HYPOTHESIS 3.3.4.2-10: As the strength of a strain increases, information inputs will more and more be interpreted (or decoded) as required to reduce the strain. (L) |
| 3.3.5 Associator |
| 3.3.5.2 Process |
| HYPOTHESIS 3.3.5.2-1: When a new information input B is associated, usually more than once, with a familiar one A that elicits a certain output, B sooner or later becomes capable of eliciting the same output as A. (L) |
| HYPOTHESIS 3.3.5.2-2: A system associates a given strain within it with actions which relieve it, so that such a strain comes to elicit the motor acts. (L) |
| HYPOTHESIS 3.3.5.2-3: A system does not form associations without (a) feedback as to whether the new output relieves strains or solves problems and (b) reinforcement, i.e., strain reduction by the output. (L) |
| HYPOTHESIS 3.3.5.2.4: Associations established early in the life of a system are more permanent than those established later. (L) |
| HYPOTHESIS 3.3.5.2-5: In associating, there is an optimal ratio of correct trails to error trials, depending on the probability that specific signals will regularly coincide in the system's environment. In most experimental environments and all natural environments this probability is less than 1, and if association were to occur with too few error trials, a system could not properly allow for probable future variations in the appearance of signals. Since the probability of the signals regularly coinciding also is nearly always greater than 0, if association occurs with too many error trials, the system cannot profit soon enough from past inputs. (L) |
| HYPOTHESIS 3.3.5.2-6: In general, association is slower the higher the level of the system. (M) |
| 3.3.6 Memory |
| 3.3.6.2 Process |
| HYPOTHESIS 3.3.6.2-1: The longer information is stored in memory, the harder it is to recall, and the less likely it is to be correct; but the rate of loss is not regular over time. (M) |
| HYPOTHESIS 3.3.6.2-2: Information stored in the memory of a living system increasingly over time undergoes regular changes-- e.g., omissions, errors, or additions of noise, and distortions-- resulting from processes of selection, reorganization with other stored information, interpretation, and entropic decay of organization. (M) |
| HYPOTHESIS 3.3.6.2-3: The removal from a system of information representing experience stored in the memory (as distinguished from the information constituting its template, whose removal is often fundamentally damaging or lethal) predictable alters stochastic measures of the system's subsequent behavior, an the degree of these changes increases as the amount removed is increases. (M) |
| HYPOTHESIS 3.3.6.2-4: The higher the echelon of a multi-echelon system, the less are its activities determined by the information of the system's template and the more are they determined by the information of experience stored in its memory. (L) |
| HYPOTHESIS 3.3.6.2-5: The higher the level of a system, in general the more complex are its memory storage and search rules, but also the more efficient they are in terms of energy cost per bit of information. (L) |
| 3.3.7 Decider |
| 3.3.7.2 Process |
| HYPOTHESIS 3.3.7.2-1: Every adaptive decision is made in four stages: (a) establishing the purpose or goal whose achievement is to be advanced by the decision, (b) analyzing the information relevant to the decision, (c) synthesizing a solution selecting the alternative action or actions most likely to lead to the purpose or goal, and (d) implementing the decision by issuing a command signal to carry out the action or actions. (L) |
| HYPOTHESIS 3.3.7.2-2: In systems which survive, the component with the most relevant information available to its decider is the one most likely to exercise power over or elicit compliance from other components in the system. (M) |
| HYPOTHESIS 3.3.7.2-3: The fewer the transmitters of information relevant to a decision, the greater is the probability that each will affect the decision. (H) |
| HYPOTHESIS 3.3.7.2-4: The signature identifying the transmitter of any message is an important determinant of the probability of the receiver complying with it. (M) |
| HYPOTHESIS 3.3.7.2-5: The longer the time during which a system has made decisions of a certain sort, the less time each decision takes, up to a limit. (L) |
| HYPOTHESIS 3.3.7.2-6: The shorter the decision period, the less thorough in general is the search within the information processing network for relevant facts and alternative solutions. (M) |
| HYPOTHESIS 3.3.7.2-7: A subsystem or component which makes decisions taking into consideration new information on the average gets it from transmitters in closer contact with the origin of the new information that a subsystem or component which uses such new information later. (M) |
| HYPOTHESIS 3.3.7.2.8: The more bits of information there are in a new message of input information, the more slowly it affects the decisions of subsystems or components. |
| HYPOTHESIS 3.3.7.2-9: A system which decides to take novel action soon after the state of its environment reaches the point at which such action is possible, does so on a smaller scale than does one which decides later. (L) |
| HYPOTHESIS 3.3.7.2-10: Initial decisions are more likely than later ones to favor a course of action that does not rule out subsequent alternatives. (M) |
| HYPOTHESIS 3.3.7.2-11: The longer a decider exists, the more likely it is to resist change. (L) |
| HYPOTHESIS 3.3.7.2-12: A decision about an information input is not made absolutely but with respect to some other information which constitutes a frame of reference with which it can be compared. (H) |
| HYPOTHESIS 3.3.7.2-13: Decisions overtly altering major values of a system are finalized only at the highest echelon. (L) |
| HYPOTHESIS 3.3.7.2-14: A system which survives generally decides to employ the least costly adjustment to a threat or a strain produced by a stress first and increasingly more costly ones later. (M) |
| HYPOTHESIS 3.3.7.2-15: A system that survives generally decides to use first the adjustment processes which can be most immediately applied to relieve a threat or a strain produced by a stress and later those which are less quickly available. (L) |
| HYPOTHESIS 3.3.7.2-16: The deciders of a system's subsystems and components satisfice (i.e., make a sufficiently good approximation to accomplishment in order to survive in its particular environment) shorter-term goals than does the decider of the total system. (M) |
| HYPOTHESIS 3.3.7.2-17: A system cannot survive unless it makes decisions that maintain the functions of all its subsystems at a sufficiently high efficiency and their costs at a sufficiently low level that there are more than enough resources to keep it operating satisfactorily. (H) |
| HYPOTHESIS 3.3.7.2-18: Systems which survive make decisions enabling them to perform at an optimum efficiency for maximum physical power output, which is always less than minimum efficiency. (M) |
| HYPOTHESIS 3.3.7.2-19: Ordinarily if two adjustment processes are of equal cost, a system decides to use the one which most rapidly or efficiently returns a variable to a steady state. (L) |
| HYPOTHESIS 3.3.7.2-20: Ordinarily when (a) two or more variables in a system are displaced from a steady state, and (b) they cannot be returned simultaneously, and (c) the costs of the adjustment process to return each variable to a steady state are identical, the system decides to use first the adjustment process which returns to a steady state the most displaced variable, and then those which return lesser displacements in order. (L) |
| HYPOTHESIS 3.3.7.2-21: The higher the level of a system the more correct ar adaptive its decisions are. (L) |
| HYPOTHESIS 3.3.4.2-5: If a transmitter with an information transmission rate (in bits per s) of R is transmitting over a noisy channel with a capacity (in bits per s) of C, and if R is greater than C, there is no way to encode the message so that the equivocation is less than R-C+e, where E is a positive fraction, less than one and usually small, of C. Moreover, as a system matures and gains practice, it encodes in ways so as to decrease the size of e. (L) |
| 4. RELATIONSHIPS AMONG SUBSYSTEMS OR COMPONENTS |
| 4.1 Structural Relationships |
| 4.1.4 Position |
| HYPOTHESIS 4.1.4-1: The position of components in a system is an arrangement which satisfies a joint function of: (a) the optimal location of nodes in distributors and nets, (b) the location of requisite inputs for particular subsystem functions, and (c) the arrangement which will make for optimal spatial distribution of functions serving all subsystems. (L) |
| 4.1.8 Density |
| HYPOTHESIS 4.1.8-1: In general, the greatest density of components in a system is at its center, then along the margins of its distributor, decreasing near the peripheral parts of the system. (L) |
| 4.2 Process Relationships |
| 4.2.2 Spatiotemporal Relationships |
| 4.2.2.4 Pattern of Action |
| HYPOTHESIS 4.2.2.4-1: The more two or more systems interact, the more they become alike in storing and processing common information. (L) |
| 5. SYSTEM PROCESSES |
| 5.1 Process Relationships Between Inputs and Outputs |
| HYPOTHESIS 5.1-1: As the information input to a single channel of a living system-- measured in bits per s-- increases almost identically at first but gradually falls behind as it approaches a certain output rate, the channel capacity, which cannot be exceeded in the channel. The output then levels off at that rate, and finally, as the information input rate continues to go up, the output decreases gradually toward zero as breakdown or the confusional state occurs under overload. (H) |
| HYPOTHESIS 5.1-2: Channels in living systems have adjustment processes which enable them to maintain stable, within a range, the similarity of the information output from them to the information input to them. The magnitude of these adjustment processes rises as information input rates increase up to and somewhat beyond the channel capacity. These adjustments enable the output rate to remain at or near channel capacity and then to decline gradually, rather than to fall precipitously to zero immediately whenever the information input rate exceeds the channel capacity. (H) |
| HYPOTHESIS 5.1-3: Among the limited number of adjustment processes which channels in living systems employ as information input rates increase are: omission, error, queuing, filtering, abstracting, multiple channels, escape, and chunking. Each of these processes applies to random and nonrandom information inputs except chunking, which applies only to nonrandom inputs with repetitious patterning to a system that can associate (or learn). Each of these processes occurs at multiple levels of living systems. Each of these processes has a cost in some sort of decreases efficiency of information processing. (H) |
| HYPOTHESIS 5.1-4: Higher-level living systems in general have the emergent characteristics of more kind and more complex combinations of adjustment processes than living systems at lower levels. (H) |
| HYPOTHESIS 5.1-5: As average information input rate increases, variation in output intensity increases. (M) |
| HYPOTHESIS 5.1-6: As average information input rate increases, the average processing time increases. (M) |
| HYPOTHESIS 5.1-7: As average information input rate increases, variation in processing time increases. (H) |
| HYPOTHESIS 5.1-8: As average information input rate increases, the percentage of internal channel capacity used in nontask communication increases. (L) |
| HYPOTHESIS 5.1-9: As average intensity of input increases, up to a point average processing time decreases. (L) |
| HYPOTHESIS 5.1-10: As average input intensity increases, use of the omission adjustment process decreases. (M) |
| HYPOTHESIS 5.1-11: As input priority increases, average output rate increases. (L) |
| HYPOTHESIS 5.1-12: As input priority increases, average processing time decreases. (L) |
| HYPOTHESIS 5.1-13: As the size of the input ensemble increases, the average processing time increases. (M) |
| HYPOTHESIS 5.1-14: As the size of the input ensemble increases, the use of all adjustment processes increases. (L) |
| HYPOTHESIS 5.1-15: As the size of the output ensemble increases, the total processing time increases. (L) |
| HYPOTHESIS 5.1-16: As the size of the output ensemble increases, the processing time per symbol decreases. (M) |
| HYPOTHESIS 5.1-17: As the size of the output ensemble increases, the processing time per symbol decreases. (M) |
| HYPOTHESIS 5.1-18: As average information input rate increases, the costs measured in energy (ergs per bit); utiles (e.g., cents per bit); time (s per bit); or duration of the state of the system (s before the state changes) remain more or less constant for a period of time and then finally increases rapidly, near the point where the performance curve begins to decrease from the maximum because the system is overloaded. (L) |
| HYPOTHESIS 5.1-19: As the percentage of total resources to meet costs (as defined in Hypothesis 5.1-18) runs out, average output rate decreases. (L) |
| HYPOTHESIS 5.1-20: As the percentage of total resources to meet costs runs out, average output intensity decreases. (L) |
| HYPOTHESIS 5.1-21: As the percentage of resource to meet cost runs out, the size of the ensemble decreases. (L) |
| HYPOTHESIS 5.1-22: As the percentage of resources to meet cost runs out, output range decreases. (L) |
| HYPOTHESIS 5.1-23: As the percentage of resources to meet cost runs out average processing time increases. (M) |
| HYPOTHESIS 5.1-24: As the percentage of resources to meet cost runs out, use of omission, error, queuing, filtering, abstracting, multiple channels, and escape adjustment processes increases. (L) |
| HYPOTHESIS 5.1-25: Channels in living systems at higher levels in general have lower capacities than those in living systems at lower levels. (H) |
| HYPOTHESIS 5.1-26: Higher-level systems in general have more variation in output intensity because they have more components which are capable of varying. (M) |
| HYPOTHESIS 5.1-27: The higher the level of a system, the greater in general is its output range. (M) |
| HYPOTHESIS 5.1-28: The higher the level of a system, the longer is its average processing time. (H) |
| HYPOTHESIS 5.1-29: The higher the level of a system, the more variation in general is there in its processing time, because there are more components as possible sources for this variation. (H) |
| HYPOTHESIS 5.1-30: The higher the level of a system, the higher is the cost per correct information unit processed. (L) |
| HYPOTHESIS 5.1-31: The higher the level of a system, the lower in general is the percentage cost per correct information unit processed. |
| HYPOTHESIS 5.1-32: The queuing adjustment process is employed more frequently the higher the peaks of information input overlap until such time as the length of the queue is greater than the local, short-term memory capacity of the system, and then the use of this adjustment falls off rapidly in a confusional state. (M) |
| HYPOTHESIS 5.1-33: As a corollary of the above, the effectiveness of the queuing adjustment process is positively correlated with the amount of local, short-term memory capacity. (M) |
| HYPOTHESIS 5.1-34: When the error adjustment process is studied as an independent variable, other adjustment processes are employed in order to minimize a positive power greater than 1 of the error and not a linear function of it. (L) |
| HYPOTHESIS 5.1-35: If previously learned or practiced information is processed, channel capacity is higher for the following reasons: |
| (a) Chunking is possible |
| (b) Only essential information is attended to and the rest is neglected. |
| (c) The need to attend only to the essential information permits rapid alternation of attention from a channel in which nonessential information is appearing to one in which essential information is appearing. |
| (d) More efficient codes are used. (L) |
| HYPOTHESIS 5.1-36: As the average information input rate approaches the average processing rate, the waiting time of elements being queued rapidly approaches infinity. (H) |
| HYPOTHESIS 5.1-37: Queues and waiting times lengthen rapidly toward infinity if the mean waiting time is greater than the mean processing time. (H) |
| HYPOTHESIS 5.1-38: As the percentage of total resources to meet costs runs out, variation in output intensity increases. (M) |
| HYPOTHESIS 5.1-39: If the ratio between the mean waiting time and the mean processing time is less than one and fixed, then the processing is best when the variation in input rate is smallest. (L) |
| HYPOTHESIS 5.1-40: A system is more likely to process information which reduces strain and thus is favorable to its hierarchy of values, rather than information which is neutral or unfavorable. (L) |
| HYPOTHESIS 5.1-41: When a given information input is qualitatively identical with one which a system has learned to process, it provides further practice with it and improves the system's ability to process it. If it is slightly different, however, it interferes with this processing ability. The less the similarity is, the less it interferes until finally it neither improves nor interferes with processing ability. (L) |
| HYPOTHESIS 5.1-42: A minimum rate of information input to a system must be maintained for it to function normally. (M) |
| 5.2 Adjustment Processes Among Subsystems or Components, Used in Maintaining Variable in Steady States |
| HYPOTHESIS 5.2-1: As stress increases, it first improves system output performance above ordinary levels and then worsens it. What is extreme stress for one subsystem may be only moderate stress for the total system. (L) |
| HYPOTHESIS 5.2-2: The greater a threat or stress upon a system, the more components of it are involved in adjusting to it. When no further components with new adjustment processes available, the system function collapses. (M) |
| HYPOTHESIS 5.2-3: When variables in a system return to a steady state after stress, the rate of return and the strength of the restorative forces are functions-- with increasing first derivatives greater than 1-- of the amount of displacement from the range of stability. (M) |
| HYPOTHESIS 5.2-4: The range of stability of a system for a specific variable under lack of strain is a monotonically increasing function of the amount of storage of the input, and under excess strain, it is monotonically increasing function of the rate of output. (L) |
| HYPOTHESIS 5.2-5: There is an inertia to the matter-energy and information processing variables which a system maintains in steady state, so that change in their ranges of stability is much less disruptive of system controls if it is undertaken gradually. (L) |
| HYPOTHESIS 5.2-6: Positive feedback may produce continuous increments of outputs which give rise to "spiral effects" destroying one or more equilibria of a system. (H) |
| HYPOTHESIS 5.2-7: When a barrier stands between a system under strain and a goal which can relieve than strain, the system ordinarily uses the adjustment processes of removing the barrier, circumventing it, or otherwise mastering it. If these efforts fail, less adaptive adjustments may be tried, including: (a) attacking the barrier by energic or informational transmissions; (b) displacing aggression to another innocent but more vulnerable nearby system; (c) reverting to primitive, nonadaptive behavior; (d) adopting rigid, nonadaptive behavior; and (e) escaping from the situation. (L) |
| HYPOTHESIS 5.2-8: A system usually associates with other systems which have arisen from similar templates rather than with those derived from dissimilar templates. (H) |
| HYPOTHESIS 5.2-9: When there are heterogeneous components in a system, they adjust to each other best if they group together into two or more partially autonomous components on the basis of similarity of their templates, functions, or values. (L) |
| HYPOTHESIS 5.2-10: Under equal stress, functions developed later in the phylogenetic history of a give type of system break down before more primitive functions do. (L) |
| HYPOTHESIS 5.2-11: After stress, disturbances of subsystem steady states are ordinarily corrected and returned to normal ranges before systemwide steady-state disturbances are. (M) |
| HYPOTHESIS 5.2-12: More complex systems, which contain more different components, each of which can adjust against one or more specific environmental stresses and maintain in steady state one or more specific variables not maintained by any other component, if they adequately coordinate the processes in their components, survive longer on the average than less complex systems. (M) |
| HYPOTHESIS 5.2-13: Under threat or stress, a system that survives, in the common good of total system survival, temporarily subordinates conflicts among subsystems or components until the threat or stress in relived, when internal conflicts recur. (L) |
| HYPOTHESIS 5.2-14: Segregation increases conflict among subsystems or components of a system, and a higher proportion of adjustment processes must therefore be devoted to resolving such conflicts, which means they cannot be devoted to advancing goals of the system as a whole. (M) |
| HYPOTHESIS 5.2-15: The larger the number of subsystems or components in conflict, the more difficult will be resolution of the conflict. (M) |
| HYPOTHESIS 5.2-16: A system tends to reduce multiple-component conflicts to conflicts among a lesser number of blocks of components. (L) |
| HYPOTHESIS 5.2-17: The greater the mutual dependence of two or more subsystems or components on a single limited input or store of matter-energy or information, the more probable is conflict among them. (H) |
| HYPOTHESIS 5.2-18: The greater the necessary interdependence in timing of processes of two or more subsystems or components, the more probable is conflict among them. (H) |
| HYPOTHESIS 5.2-19: The greater resources available to a system, the less likely is conflict among its subsystems or components. (H) |
| HYPOTHESIS 5.2-20: The decider of a system must resolve conflicts among other subsystems, which signal their demands for autonomy, and the suprasystem, which signals commands for compliance. (H) |
| HYPOTHESIS 5.2-21: When a system is receiving conflicting command signals from several suprasystems, it intermittently being a component of all of them, it tends to comply with the signals of the suprasystem most important to it. The greater the divergence between its current function the signals from that group, the more likely it is to comply. (L) |
| HYPOTHESIS 5.2-22: When a system is receiving conflicting command signals from several suprasystems, it intermittently being a component of all of them, the more different the signals are, the slower is its decision making. (M) |
| HYPOTHESIS 5.2-23: When a system is receiving conflicting command signals from several suprasystems, it intermittently being a component of all of them, the more different they are, the more likely it is to change its decisions. (L) |
| HYPOTHESIS 5.2-24: Conflicts among various sorts of alternatives are resolved by a system in different ways: |
| (a) Between two mutually exclusive positive goals, resolution is difficult if they appear to be of equal value, but choice is usually made quickly without much vacillation. |
| (b) With goals that are positive and negative at the same time, approach occurs until the system is near, then avoidance or movement from the goal occurs, and the system tends to vacillate for a time fairly near but not at the goal. |
| (c) Between two mutually exclusive negative goals, the system vacillates from one to the other but tends not to make a decision. (L) |
| HYPOTHESIS 5.2-25: Lack of clarity of purposes or goals in a system's decisions will produce conflict between it and other components of the suprasystem. (M) |
| HYPOTHESIS 5.2-26: If a system has multiple purposes and goals, and they are not placed in clear priority and commonly known by all components or subsystems, conflict among them will ensue. (H) |
| HYPOTHESIS 5.2-27: The vigor of the search for resolutions of conflict increases as the available time for finding a solution decreases. (M) |
| HYPOTHESIS 5.2-28: The search for resolution of conflict will be more vigorous if no alternative is available which reduces all strains. (L) |
| HYPOTHESIS 5.2-29: If a conflict arises from incomparability of signals, the time to resolution will be shorter than if it arises from unacceptability of them. (L) |
| 5.4 Growth, Cohesiveness, and Integration |
| 5.4.1 Growth |
| HYPOTHESIS 5.4.1-1: The rate of increase in the number of components of a young system rises exponentially until it reaches a maximum, but this growth rate may be altered by environmental or other factors. (L) |
| HYPOTHESIS 5.4.1-2: Growing systems develop in the direction of: (a) more differentiation of subsystems, (b) more decentralization of decision making, (c) more interdependence of subsystems, (d) more elaborate adjustment processes, (e) sharper subsystem boundaries, (f) increased differential sensitivity to inputs, and (g) more elaborate and patterned outputs. (M) |
| HYPOTHESIS 5.4.1-3: Increase in the number of components in a system requires a disproportionately larger increase in the number of information processing and deciding components. (L) |
| HYPOTHESIS 5.4..1-4: If the rate of information input into a system falls below a specific lower limit, normal growth of the system is impossible. (M) |
| 5.4.3 Integration |
| HYPOTHESIS 5.4.3-1: For the same level of system output, more transmission of information is necessary to coordinate segregated systems than integrated systems. (M) |
| HYPOTHESIS 5.4.3-2: As a system grows and adds more components, the components in general become increasingly independent in decision making. This is probably because the system cannot meet the increasing costs of processing the information tot he system's decider, as required for centralized deciding. (M) |
| HYPOTHESIS 5.4.3-3: As a system's components become more numerous, they become more specialized, with resulting increased interdependence for critical processes among them. (H) |
| HYPOTHESIS 5.4.3-4: Decentralization of decision making in general increases the speed and accuracy of decisions which reduce local strains. (H) |
| HYPOTHESIS 5.4.3-5: As decentralization increases, echelons or components of the system's decider increasingly make decisions without the benefit of relevant information existing elsewhere in the system. (H) |
| HYPOTHESIS 5.4.3-6: The more decentralized a system's deciding is, the more likely is there to be discordant information in various echelons or components of its decider. (H) |
| HYPOTHESIS 5.4.3-7: Up to a certain amount of stress, systems do more centralized deciding when under stress than when not under stress. Beyond that amount, deciding becomes increasingly decentralized until the system terminates or the stress abates. (L) |
| HYPOTHESIS 5.4.3-8: A component will comply with a system's purposes and goals to the extent that those functions of the component directed toward the goal are rewarded and those directed away from it are punished. (M) |
| HYPOTHESIS 5.4.3-9: As long as all relevant information flows among all echelons or components of the decider to keep them all informed of states of the system, the more decentralized the decider of a system is, the better will be the interaction of its echelons or components. (L) |
| 5.5 Pathology |
| HYPOTHESIS 5.5-2: Abnormal or "neurotic" outputs can be elicited by rewarding one information input, not rewarding (or punishing) a similar information input, and then altering one or both until they are indistinguishable. (L) |
| HYPOTHESIS 5.5-1: The farther away a component is from the point of trauma to a sys tem, the less pathological is its function, and particularly the less is its relation to the system's hierarchical organization destroyed. (L) |
| 5.6 Decay and Termination |
| HYPOTHESIS 5.6-1: If a system's negative feedback discontinues and is not restored by that system or by another on which it becomes parasitic or symbiotic, it decomposes into multiple components and its suprasystem assumes control of them. (H) |
| Community |
| Education/Special Education |
| Overview |
| Categories and General Approaches |
| Instruction |
| Basic Theory |
| Inclusion |
| Segregated |
| Weblogs |
| k-12blogWrite |
| First Log I found--in San Francisco Bay Area |
| This is the link to the blog at bayareawritingproject |
| Weblogs for Educators |
| Weblogg-Ed |
| Australian hypertext site.. education category page |
| Check it out -- plain formatting |
| here tis |
| School Blogging |
| Run out of Southern California |
| www.schoolblogs.com-has articles on class weblogs |
| Weblogs.Com: Recently Changed Weblogs - Userland, Weblogs.Com Welcome to the all-new fast Weblogs.Com! Recently Changed Weblogs. Updated: 7/6/2002; 2:11:02 AM Pacific. Welcome ... |
| IT Scoop || Collaborative Media for Instructional Technology ... - Welcome to Scoop, Latest News. ... |
| MyJamby MeetingPoint - myjamby.com Create a new Weblog. Navigation. Home About. Discussion. Recent Discussion Create New Topic. Members. Join Now Login. United ... |
| The Shifted Librarian - The Shifted Librarian : Shifting libraries at the speed of byte! My name is Jenny, and I'll be your information maven today. Updated: 7/6/2002; 12:13:24 AM. ... |
| TELLIO - TELLIO, Teaching Ourselves. ... |
| Edublog Starter Kit-Sara Lohnes (middlebury.edu) |
| eduBlogs-Posted by Sarah, 6/17/02 at 3:11:37 PM. |
| When I first started looking at weblogs and considering their use in education a year ago, I wrote a brief post with my thoughts. At the time, I couldn't find many classes that were using weblogs. |
| The past year has seen tremendous growth in the use of weblogs in education, in part due to the rising popularity and media exposure of weblog tools. As a result, I've heard lately from several people who are looking to get started with weblogs or explore the idea of weblogs in education. So, what follows is my "weblog starter kit". This list also includes information about running Frontier on OS X, as I get a number of questions about this as well. |
| * Disclaimer: this is by no means a comprehensive list! If you have a site and you would like to be listed, please let me know. The growth of this community is vital to the exchange of ideas and information! |
| -- Some schools/educational institutions/classes using weblog: |
| Higher Ed |
| CET |
| Middlebury College |
| UC Berkeley Interactive U |
| University of Michigan |
| Richard Stockton College |
| Centenary College |
| University of Wisconsin |
| Private and Public Schools |
| Bay Area Writing Project |
| Martin Luther King School in SF |
| MLK Main Link |
| British School of Amsterdam |
| -- Blogs about weblogs in education |
| [alterego] |
| Schoolblogs |
| The Main Schoolblogs link |
| Weblogg-Ed |
| k12BlogWrite |
| Pat Delaney |
| Terry Elliot |
| -- Other Weblog Tools |
| Blogger |
| Moveable Type |
| Slash |
| Greymatter |
| The Complete Guide to Weblogs - Tools (this has got them all) |
| Assessment |
| Work Flow and Projects |
| 12/1/02; 7:18:53 AM by SPH-Developing and Publishing the Group Acceleration Cluster of Ideas |
| I have to get these ideas down so I won't lose them. I'll notify that there are some thoughts are brewing and contributions are welcome via a seeds entry. Maybe make it slightly outrageous to get attention. |
| -The next set of thoughts deserves development in the group forming work group. I can then make it more broadly available. have to work out sequence |
| Wide-Narrow-Wide(W1-N-W2)-- My thinking style that ultimately leads to relatively accessible writing. |
| Write about the situation and inquiry showing all relevant thoughts and links any way you can. Issue is making first map of what is intuited but not yet expressible. Surface the core structure of the piece-- translate into outline. Use outline to refine the huge first draft into a more elegant set of sequenced pieces. Reintegrate into an elegant story. Publish story in small segments for blogging public -- giving access to full story whenever any want more. |
| Parts of the whole (W1 of W1-N-W2) piece: |
| An hypothesis about the acceleration power of a bounded system of thinkers (the system meeting certain criteria) |
| an analysis of system structure and process specs(starting with Bryan Coffman's introduction --see System under My outline) |
| one-by-one as they might affect a bounded system of thinkers |
| some of the first thoughts about system theory driven implications are: a decider, an exclusivity of focus (for example a per cent of klogging time guarantee) compact between members, division of responsibility to cover system survival functions as well as system growth. |
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© copyright 2003
by S. Pike Hall.
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