The volumetric model — 5 change levels, 14…

This material is a specification and reference set with a reference rule engine. It is not an editing application, a rendering pipeline or a completed production, and the worked example is entirely fictional — it exists to demonstrate the method.

The five change levels

The fourteen measurement lenses

Every change — a re-edit, a reframe, a regenerated shot — is read through the same fourteen questions.

The ten decision variables

The chapter

The five change levels. Source: rules/dimensions.json.
Level	Ordinal	What may change	Default max changed dimensions
baseline	0	Preserve structure and treatment; clean, repair, and clarify.	0
minor	1	Change one or two local properties without changing the beat.	2
major	2	Change the treatment of a beat or scene while preserving its core function.	5
structural	3	Change coverage, sequence, timing architecture, or narrative organization.	12
paradigm	4	Change format, perspective, genre, medium, narrator, or governing premise.	unbounded

01 — LAKA Volumetric Model

1. The production decision envelope

Every production decision uses the same internal variables.

Variable	Question
Object	What is being acted upon?
Conditions	Under what circumstances does the system operate?
Actions	What does the system do?
Tools	What mechanisms carry out the action?
Resources	What information, assets, people, compute, or capital are required?
Outcomes	What does the system produce?
Feedback	How does the result change later decisions?
Constraints	What limits performance, legality, continuity, or adoption?
Value	For whom is value created, and what kind?
Failure mode	How can the decision fail?

2. Five change levels

Level	Meaning	Media example
0 — Baseline	Preserve structure and intent	Remove noise, correct transcript, switch to active speaker
1 — Minor change	Change a local property	Slight punch-in, lower-third, shorten a pause
2 — Major change	Change treatment of a beat	Replace talking head with B-roll sequence and diagram
3 — Structural change	Change organization or coverage	Move a reveal earlier, rebuild an act, generate missing scene coverage
4 — Paradigm change	Change governing model	Convert interview into narrated investigation, animation, or first-person essay

A change level is not a quality score. A baseline solution can be the best solution.

3. Fourteen LAKA meta-variables

Each variable uses a normalized value from 0.0 to 1.0, plus a human-readable state.

Meta-variable	First-principles question	Example in editing
Magnitude	How much changes?	Two-frame trim versus full scene replacement
Rate	How quickly does the state change?	Slow reveal versus smash cut
Direction	Toward what state?	Toward intimacy, clarity, threat, relief, proof
Scope	How broadly does it apply?	Word, clip, beat, scene, episode, series
Depth	How fundamental is the change?	Surface styling versus meaning or structure
Duration	How long does the effect persist?	Flash frame versus entire act
Frequency	How often does it recur?	One punch-in versus recurring visual motif
Acceleration	Is the rate increasing or decreasing?	Cuts become progressively faster
Variability	How consistent or unpredictable is it?	Uniform pacing versus deliberate irregularity
Detectability	How visible is the intervention?	Invisible continuity edit versus obvious glitch
Reversibility	Can it be undone without loss?	Metadata marker versus destructive render
Propagation	What downstream objects change?	Moving one beat shifts captions, music, graphics, chapters
Amplification	How much does the audience effect multiply?	Silence before a confession amplifies emotional impact
Accumulation	How do repeated effects build?	Repeated visual motif becomes a theme

4. LAKA change vector

{
  "magnitude": 0.35,
  "rate": 0.20,
  "direction": ["intimacy", "credibility"],
  "scope": ["beat"],
  "depth": 0.25,
  "duration": 8.4,
  "frequency": 1,
  "acceleration": 0.0,
  "variability": 0.15,
  "detectability": 0.20,
  "reversibility": 1.0,
  "propagation": ["captions", "music_cue"],
  "amplification": 0.70,
  "accumulation": 0.10
}

5. Volumetric dimension families

A candidate can carry values in all of these families.

Source — origin, media type, rights, authenticity, quality.
Time — source range, output range, duration, handles, synchronization.
Language — words, syntax, speaker, intent, confidence, translation.
Semantics — entities, topics, propositions, claims, evidence.
Discourse — question/answer, support, contrast, cause, reference.
Narrative — beat role, tension, stakes, reveal, payoff, arc.
Audience — knowledge, emotion, needs, objections, accessibility.
Performance — energy, pace, clarity, authenticity, gesture, gaze.
Shot — scale, angle, lens, distance, focus, composition, movement.
Lighting — role, direction, quality, ratio, color, dynamics.
World — location, set, props, wardrobe, weather, time of day.
Edit — boundary, cut type, transition, duration, rhythm, continuity.
Graphics — information relation, encoding, placement, motion.
Audio — dialogue, music, ambience, dynamics, spatial state.
Color/VFX — transforms, look, compositing, tracking, cleanup.
Delivery — aspect, resolution, codec, language, channel, duration.
Governance — rights, consent, disclosure, provenance, approvals.
Measurement — quality signals, engagement, errors, feedback.

6. Candidate-generation algorithm

1. Determine the object and intended audience-state change.
2. Load hard constraints.
3. Select allowed dimensions.
4. Choose a LAKA change level.
5. Generate candidate values inside the allowed range.
6. Reject candidates that violate truth, rights, context, continuity, or delivery constraints.
7. Score survivors.
8. Select a diverse set across meaningful dimensions.
9. Render previews.
10. Gather human and performance feedback.
11. Update weights without overwriting source truth.

7. Utility function

A configurable starting point:

Utility(candidate)
= 0.16 StoryFit
+ 0.14 Clarity
+ 0.12 ContextIntegrity
+ 0.11 EmotionalEffect
+ 0.10 EvidenceStrength
+ 0.09 Continuity
+ 0.08 VisualOrAuralQuality
+ 0.07 AudienceFit
+ 0.05 Accessibility
+ 0.04 BrandFit
+ 0.04 TechnicalReliability
- DistortionRisk
- RightsRisk
- FabricationRisk
- FatigueCost
- ComputeCost

Weights must change by project. A documentary gives more weight to evidence and provenance. A comedy clip gives more weight to setup, timing, and reaction. An educational video gives more weight to clarity and transfer.

8. Diversity selection

High-scoring candidates often collapse into one style. Use a distance function.

SelectedSet
= maximize(sum(utility))
+ diversity_weight × pairwise_distance

Distance can include:

shot scale, angle, lens, movement, lighting ratio, color,
graphic mode, cut rhythm, sound treatment, narrative perspective

9. Propagation graph

A decision is not isolated.

Move beat
→ changes timeline positions
→ shifts music cue
→ shifts captions
→ changes graphic timing
→ changes chapter markers
→ changes short-form derivatives
→ may change hook and retention prediction

Every decision stores affected_objects and recompute_required.

10. Feedback grammar

OBSERVE metric
COMPARE against target and prior version
LOCATE responsible objects
CLASSIFY failure mode
APPLY smallest sufficient LAKA change
RENDER alternative
VALIDATE meaning and quality
PROMOTE or revert

11. Failure-mode classes

Meaning distortion
Missing context
Weak causality
Redundancy
Pacing mismatch
Visual discontinuity
Audio discontinuity
Technical failure
Accessibility failure
Factual or evidentiary failure
Rights or consent failure
Generated-media artifact
Format/platform failure
Excessive change
Insufficient change
Metric overfitting

12. Example: emotional disclosure

Object: confession beat
Condition: high vulnerability, clear face, no evidence graphic needed
Action: hold close-up; slow or stop camera movement; lower music
Outcome: intimacy and credibility
Constraint: do not remove qualifying language
Failure mode: manipulative over-scoring or distracting cuts

LAKA interpretation:

Magnitude: low-to-moderate
Rate: slow
Direction: intimacy
Scope: one beat
Depth: emotional, not factual
Duration: complete thought plus afterbeat
Frequency: rare
Acceleration: none
Variability: low
Detectability: low
Reversibility: high
Propagation: music, captions, adjacent cut points
Amplification: high
Accumulation: moderate if repeated confessions form an arc