Lokapal

Schematic Vectors

On back-and-forths.

Schematic Representation is how a record is kept. Once a record exists, material can move in three directions relative to it: into the record, among records already kept, and out of the record. Those directions are the schematic vectors. AI tools may travel two of them. One stays with the user.

The same three directions apply to any library of placements — a glossary of terms, a set of case readings, a structured note of a diagram. The fields change from one library to the next. The rule about who may fill them is the same.

  • SCHEMATIC VECTORS: The three directions relative to a schematic record — supply, probe, and expound — together with the rule of which directions an AI tool may travel.

For these definitions, non-schema means anything that is not already the stored record: a statute, a page of notes, a paragraph, a diagram. The word names a direction. It is not a fifth representation type.

  • SUPPLY VECTOR: Non-schema to schema. The user commits a placement into a schematic record — this jurisdiction, this pair, this side. Closed to AI tools.
  • PROBE VECTOR: Schema to schema. A supplied record is tested against its own fields, against the equations, or against other supplied records. Open to AI tools.
  • EXPOUND VECTOR: Schema to non-schema. A supplied record is set forth as prose, notation, or a diagram. Open to AI tools.

The three sections below take one example through each vector. A city requires that council candidates have five consecutive years of residency, and does not require that they were born in the city. What follows is one reading of those requirements, not the only reading, and not the ordinance itself.

Supply

Supply is writing a placement into the record. The candidate requirements are source material. They become a record when the user fills the fields and stands behind them.

The user reads the requirements through Operation, on the Identity Axis: Fronterization for the restriction, Permeability for the allowance. They write:

id: council-member-requirements
jurisdiction: operation
pair: fronterization / permeability
fronterization: candidates must have five consecutive years of residency in the city
permeability: candidates need not have been born in the city

Those fields are a judgement. An AI tool that chooses the jurisdiction, the pair, or the side has authored the reading. Supply is closed to AI tools. Writing the fields directly, with no prose in between, is still supply.

An AI tool can offer a proposed reading. Storing that proposal as the entry still leaves the AI as the author of the fields. The user has to make the placement. If an AI tool filled the fields, later comparisons compare the tool’s readings.

Probe

Probe begins after supply. Its object is a record the user has already committed.

On the council-member-requirements record, an AI tool can check that both sides of the Fronterization/Permeability pair are filled, that the terms match the glossary, and that the record does not affirm both Functionality and Perdurability, which the Incompatibility Axiom forbids. It can also compare this record with other supplied cases — other eligibility rules, other Identity Axis readings — and count how many accepted readings share a jurisdiction. Once enough records exist, the same kind of test can run across the library: every recorded instance, say, of an Identity Axis asymmetry that preceded a Unification-type outcome, across otherwise unrelated cases. Those tests describe judgements already made. They add checks, counts, and patterns. They do not add a new case.

An AI tool may run these tests. It may not fill a side the user left open and call the filling a finding. If Permeability had been left blank, flagging the gap is a probe. Writing a value into that field is supply, and supply is closed to AI tools.

If the output is a fresh record that was not in the library before, the direction has changed. That new record is supply.

Expound

Expound sets a supplied record forth so a reader can follow it. The record remains the source of truth. The prose, the notation, and the diagram are views of that record.

From the council-member-requirements record, an AI tool can write a paragraph that explains the reading, set the pair in notation, or draw the Identity Axis with Fronterization and Permeability placed as the fields already state. Notation and a diagram should be projected from the fields and from the glossary.

Prose can be a draft. A reader can see when a sentence uses a word the record did not contain, and can refuse the draft. Editing the draft does not correct the record.

Filling new fields from the paragraph, the figure, or a spoken account is supply: material that is not the record comes in, and a placement goes out. The paragraph that explains this reading is useful. The stored record remains the case.