Abstract

This document proposes a new way of writing and thinking called cCCML (an extension of cVJML). It tries to fix limits of normal, sentence‑by‑sentence language: it can bias your attention, overload short‑term memory, and let details fade while you’re still reading or talking. cCCML “packs” related ideas together utilizing smallest, shortest, and least energy dense motor movements so your brain can chunk them, organize traces, and switch between these faster, which appears to make it easier to build and adjust complex thoughts. This could improve how individuals and groups load and work with ideas in memory. But it’s still a hypothesis: there isn’t solid experimental proof yet, and the long‑term effects of using it are unknown, so readers should be cautious.

To show ideas, cCCML uses special bra-kets inspired by math and physics. Angle bra-kets like <A|B> hold two ideas at once (a “superposition” or tight comparison) and pairs with cVJML’s square brackets [ ] which can set levels or create branches. Bra<c|kets can be nested, split, woven, or entangled to combine, choose between, or relate ideas. Examples include <samsara|nirvana> and <emptiness|form>, or placeholders like <rudder|oar>. The author also suggests the system may help memory by grouping words that look or sound alike, similar to a “memory palace.” A writing tool for cCCML is being developed, but for now the approach is experimental.

Introduction

It is hypothesized that <level|depth> of processing (Craik, 1972) is correlated highly with cCCML, which is proposed to solve for three salient issues in serialized linguistics: (a) attentional bias due to pre-cueing (see Posner, 1978) by serialized language, (b) packing problems (see Kepler, 1611/1962) of working memory’s capacity limitations (Cowan, 2001; Luck & Vogel, 1997; Miller, 1956) against serialized [and parallel] language, and (c) race conditions of working memory’s vanishing content during serialized [and parallel] communication of its contents (see Sperling, 1960).

Until further scientific experiments may validate this hypothesis, it is suggested that c<CC|VJ>ML practitioners exercise caution so as to not “jump off the pyramid”, without considering potential intercepts with its sides. cCCML is an extension to cVJML which “tilts” cVJML for super-positional/probabilistic operations (more on this later). Long term effects of c<CC|VJ>ML utilization is not yet know, nor is there a longevity study in progress to monitor for long term effects.

As c<CC|VJ>ML solves for the aforementioned problems with existing serialized languages, it solves for another issue, that of resource utilization during working memory loading. Since c<CC|VJ>ML increases construct and relational density simultaneously, sans temporal constraints, it is easier to load rich constructs and relations onto working memory more rapidly. Considering the effects of chunking (Miller, 1956), c<CC|VJ>ML is proposed to increase chunking density. These effects are proposed to allow more rapidity and flexibility in modifying working memory contents as one works with a ”Glasserian sorting table”. This is hereby termed ”Glasserian memory” in honor of Barney G. Glaser who co-originated and co-founded the grounded theory (GT) perspective.

For the remainder of this text, cCCML will be used, where cVJML extensions allows for multiple valences to be wielded by operators by a tilting process which is proposed to be highly correlated with [redacted] characteristics of neurophysiology. For readers opting to engage in cCCML or cVJML, or the paired c<CC|VJ>ML, a software package for writing with these markups is under product development, and borrows from Item Response Theory (DeMars, 2010; Templin, 2016) to manage optimal arousal for flow -induction and -maintenance.

Primer

[ALT] + [N]

[<], [|], [>]

For the remainder of this text, language will not follow conventional guidelines. It is a change of fields of function- disturbance first waves that MVL captures in more temporal resolution [demonstrating non-commutativity at specific valences [e.g., 4, 8, 16, 32, … , N]]. Bra-ket notation is borrowed from quantum electrodynamic (QE) mathematical notation, however we place wave or function, or wave and function in a bra and ket instead of multiple bras or kets (see below).

Example 1

The super positioning of two concepts are represented by bra-ket notation, borrowing from quantum electrodynamic (QE) mathematical notation.

[<輪廻|涅槃>]
samsara is exactly nirvana

Note

Utilizing proper QE notation would result in two kets of vectors |輪廻> + |涅槃> = [redacted] without the inclusion of a proper bra-. For advanced practitioners, this system can be denoted more properly by: <涅槃|輪廻>, as the linear form of <f| acts on vector |v>. The way this is read is that 涅槃 acts on 輪廻, where the acting in this case is nekkhama, that is, a braking of activity, where that providing the brake is [redacted]. As this is a complex nuance to the adoption of MVL, MVL dispenses with this extreme precision in favor of a super positional notation. Future iterations of MVL may solve for the packing problem presented.

Example 2

The super positioning of concepts may be to the N valence, where three may be written as follows. While this is a starting point, it may be simplified in example 3 using cVJML.

<輪廻|◯|涅槃>

Example 3

Example 2 may be simplified by using an cVJML valence.

[◯]
<輪廻|涅槃>

Example 4

Grounded Theory interchangeable indicators may bra-keted and serve as placeholders for isomorphic functions.

give regards to the boatman, there is
a <rudder|oar> that once exposed,
can never be forgotten, to us.

Example 5

Given example 1, 2, 3, and 4, the clear extension is applied in Buddhist categorization of phenomena as follows.

<emptiness|form>

Formalization

cCCML uses the following bra-ket notation structure horizontally:

<HC1|…|HCn>

Where HC1 presents a cohered concept within the bra-keted conceptual frame and HCn>1 represent additional concepts in coherence within the same bra-keted conceptual frame.

In this case, the first cohered concept left, with additional cohered concepts continuing right in left-to-right languages.

Where the sequence of 1…n may represent “entangled” coherence between each element HC1HCn across a set of bra-kets.

<HC1|…|HCn> and <HC1|…|HCn>

Or vertically:

[LIMITATION]

In this case, the first cohered concept is located top, with additional cohered concepts continuing downward in left-to-right languages.

Nesting

Bra-kets may follow rooting/exponentiating and/or recursion/iteration processes.

Example 1

<emptiness|<form|sight|seeing>>

Guidance

This is essential for gimbal operations.

Entanglement

cCCML Editor:
[|] [1…9]

Bra-kets may be entangled, where multiple units of bra-ket notation may collapse left or right.

Example 1

<form|1emptiness> <samsara|1nirvana>

Example 2

In abridged cCCML notation where entanglement is implied by default, entanglement graphs may be omitted.

<form|emptiness> <samsara|nirvana>

Example 3

The following bra-kets <worship|<workshop|workship>>; note that Packing Problem still favors MV (see MVL Factoring).

/* abridged */
The fruits are maturing, this was behind the wor<|k>sh<i|<o|i>p windows… limitless benefit…
/* unabridged */
The fruits are maturing, this was behind the wor<|1k>sh<i|1<o|i>p windows… limitless benefit…

[What is the weaving bracket to traverse the “i”?]

Guidance

This is similar to a “choose your own adventure” story, where if a reader reads only the left of the first bra-ket, then the reader reads the right of the second bra-ket. This emulates probability collapse.

Branching

cCCML may be forked by embedding a bra-ket within an cCCML valence.

Example 1

[<no action at a distance|[STATIC]>]
That’s it, the movement of time
it moves forward at a uniform, speed

Example 2

[[<spooky|1not-spooky>]]
[<no action at a distance|1[STATIC]>]
That’s it, the movement of time
it moves forward at a uniform, speed

Guidance

This is only to be used when realizing branch super-positioning, and is used by advanced practitioners.

S[<p|l>]it, Split, or Slit Bracketing

This bracket is for <quantized|non-quantized> bifurcation operations.

Guidance

Slit Bracketing is evident in superpositional atemporal/aspatial awareness, where a realization intercedes in a conceptual topology, and un-measures [conjecture: (aka: hologram projection back-propagation)] through swapping p|l matter through quantum de-measurement (aka: black hole wave-function tesselation).

Bracket Notation; Experimental Syntax

Weave-Bracketing

cCCML Editor:
[ CTRL ] + [ [ ]
[ CTRL ] + [ ] ]

Weaving brackets are used when joining intra-brackets.

Example 1

To use semi-conductors as an analogy, the 'n'
below is a doping material which allows the
concept 'low' to generate 'burn'.
[ { low } n { burn } ]

cCCML Bar Diode

A Bar Diode signifies an intra-bra-ket weave.

Example 1

<s~|cept>

Mathematical Conversion

This is where cCCML devolves into mathematical representation.

Guidance

This is just a necessary expansion for complex conceptual interaction, and grounds us into the descriptive via diagrammed representation.

Applications

Functional Form Inversion

cCCML Editor:
[ CTRL ] + [ – ]
The command for expanding a bracket around prior brackets.

Functional form inversion rotates linguistics by applying functional representations (i.e., function) around a phenomenological cluster (i.e., name).

Example 1

<Desk|Raised Service Function>

See Primer Note, for the expansion of this notation to something more QE compatible (i.e, “<raised service function|desk>”).

References

Baddeley, A. D. (2007). Working memory, thought, and action. Oxford University Press.

Baddeley, A. (2010). Working memory. Current Biology20(4), R136-R140. https://www.cell.com/current-biology/pdf/S0960-9822(09)02133-2.pdf

Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G. A. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (vol. 8, pp. 47-89). Academic Press.

Baddeley, A. D., Lewis, V., & Vallar, G. (1984). Exploring the articulatory loop. The Quarterly Journal of Experimental Psychology, 36A, 233–252.

Baddeley, A. D., Thomson, N., & Buchanan, M. (1975). Word length and the structure of short-term memory. Journal of Verbal Learning and Verbal Behavior, 14, 575–589.

Coltheart, M., Davelaar, E., Jonasson, J. T., & Besner, D. (1977). Access to the internal lexicon. In S. Dornic (Ed.), Attention and performance VI (pp. 535–555). Hillsdale: Erlbaum.

Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage. Behavioral Brain Sciences, 24(1), 87–185. https://doi.org/10.1017/s0140525x01003922

Craik, F. I., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning & Verbal Behavior, 11(6), 671–684. https://doi.org/10.1016/S0022-5371(72)80001-X

DeMars, C. (2010). Item response theory. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195377033.001.0001

Jalbert, A., Neath, I., Bireta, T. J., & Surprenant, A. M. (2011a). When does length cause the word length effect? Journal of Experimental Psychology. Learning, Memory, and Cognition, 37, 338–353.

Jalbert, A., Neath, I. & Surprenant, A.M. (2011b). Does length or neighborhood size cause the word length effect?. Memory & Cognition, 39, 1198–1210. https://doi.org/10.3758/s13421-011-0094-z

Kepler, J. (1962). Dioptrice. W. Heffer. (Original work published 1911)

Luce, P. A., & Pisoni, D. B. (1998). Recognizing spoken words: The neighborhood activation model. Ear and Hearing, 19, 1–36.

Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279–281. https://doi.org/10.1038/36846

Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97. https://doi.org/10.1037/h0043158

Posner, M. I. (1978). Chronometric explorations of mind. Lawrence Erlbaum.

Rogers, T. B., Kuiper, N. A., & Kirker, W. S. (1977). Self-reference and the encoding of personal information. Journal of Personality and Social Psychology, 35(9), 677–688. https://doi.org/10.1037/0022-3514.35.9.677

Roodenrys, S. (2009). Explaining phonological neighbourhood effects in short-term memory. In A. Thorn & M. Page (Eds.), Interactions between short-term and long-term memory in the verbal domain (pp. 177–197). Psychology Press.

Sperling, G. (1960). The information available in brief visual presentations. Psychological Monographs: General and Applied, 74(11), 1–29. https://doi.org/10.1037/h0093759

Templin, J. (2016). Item response theory. The Encycloypedia of Adulthood and Aging.

Appendix II: Change Modification Log

06 NOV 25 - Updated abstract; refactored headers; moved change modification to appendix to reflect site information re-architecture to arrive at greater clarity.
12 SEP 25 - BREAKING CHANGE - Refactored MDL to cCCML for clarity, disambiguation, and differentiation; cleaned up references to cVJML.
25 SEP 23 - Clarified pointer with additional references, and added a non-copyrightable Google Bard interpretation.
23 SEP 23 - Alignment of pointer/primers.
16 OCT 21 - Clarified pointer, refactored Example 1, and added note regarding the technical mapping to bra-ket notation in QE.
23 JUN 21 - Added a nested entanglement example.
22 JUN 21 - Added placeholder page for MVL.
22 JUN 21 - Moved topics from MDL specific to braket notation to MVL.

Appendix II: Research Memos

Working Theory
This is a working theory and is in casual progress.
It is worth considering some convergence with psychological studies investigating the phonological loop in working memory (Baddely & Hitch, 1974; Jalbert et al., 2011b). Word length had been found to evidence differences in the ability to remember lists of words (Baddeley et al., 1984; Baddeley et al., 1975). However further studies had found that the differences between recall of words with a small and large neighborhoods (i.e., words that differed by a n-letters vs. words that differed in > n-letters; Jalbert et al., 2011a). Words that differ by only one letter are termed orthographic neighbors (Coltheart et al., 1977; Luce & Pisoni, 1998).
Since MVL demonstrates a high degree of organizing information based on orthographic neighborhoods, it is proposed that cVJML (and cCCML) had become additional Methods of Loci. In this method, an orthographic axis (i.e., the letters changing) is as a room in and of itself that morphemes had been pegged to. This eliminated needs for reliance on a "default" self-reference effect (SRE; Rogers et al., 1977). That said, concurrent articulation abolishes the neighborhood size effect (Jalbert et al., 2011b).
[Against these effects is evidence that remembrance of lists is inhibited by the limit of the phonological loop (~2 seconds; [TODO]). The word length effect is reasoned to give lists of words easier rememberance throught the gaps between the shorter words (Baddeley et al., 1984). There is also a process proposed that redintigrates words with larger neighborhoods (Roodenrys, 2009). Note that concurrent articulation is favored over the concept of articulation suppression (see note 1 in Jalbert et al., 2011b). Articulation suppression is where the spoken word interferes with rehearsal and its benefits (Baddeley, 2007, 2010; Baddeley & Logie, 1999). That said, articulation suppression had not been found in expert interpreters (Padilla et al., 1995).]
[Mental rotation is longer if degrees of rotation is longer (Shepherd & Metzler, 1971).]
[Chunking increases the visuospatial skethchpad's pattern recognition (Brooks, 1968).]
[The working memory of the visuospatial sketch pad is also suppressed by dual tasking (Brooks, 1968).]
[Frontal lobe plays central role in working memory's executive attention of the central executive.]
[Epsiodic buffer is connected to LTM and is coordinated with the phonological loop and visuospatial sketch pad.]
[Episodic buffer is in early stages of development (Baddeley et al., 2009).]
[Those with higher reading spans demonstrate a central executive with greater ability to filter out distractors (Gaspar et al., 2016).]
A technology invention for the purpose of signal attenuation in information-gimbal mechanics of neural signal processing. This is a foundation for [REDACTED].