Textual Close-Reading Mode

batch: Second Sweep Candidate Batch 01

canonical_family: Interpretation, Evidence & Representation

aliases:
Evidence-Bound Close Reading
Mark-to-Meaning Close Reading
Fine-Grained Textual Interpretation
Grain-Exhaustive Reading
Substrate-Attentive Close Reading
Textual Detail Warranting

source_primes: close_reading interpretation evidence representation

related_primes: frame_of_reference context comparison hermeneutic_circle parsing form_and_content order composition motif pattern_recognition uncertainty traceability validation

slug: interpretation

slug: evidence

slug: representation

slug: context

slug: comparison

slug: parsing

slug: composition

slug: motif

slug: uncertainty

slug: traceability

slug: validation

components: Recurrence, Contrast, and Omission Register

components: Edition, Translation, and Collation Control

mechanisms:
Line-by-Line Annotation Protocol
Close-Reading Table
Diction, Syntax, and Punctuation Trace
Motif Concordance and Recurrence Map
Sequence and Placement Map
Omission and Negative-Evidence Audit
Micro-to-Macro Claim Matrix
Parallel-Passage Comparison
Edition or Variant Collation Table
Paraphrase-Difference Test
Counterreading Stress Review
Interpretive Saturation Log
Contextual Reentry Memo

essence_one_line: Suspend premature paraphrase, inspect the artifact at its meaningful grain, and bind every larger interpretation to exact marks, relations, repetitions, placements, and omissions.

compression_statement: Textual Close-Reading Mode addresses a recurring interpretive failure: a reader compresses a text into topic, summary, intention, or doctrine before examining how wording, syntax, sequence, formal arrangement, recurrence, contrast, and absence produce or constrain meaning. The archetype temporarily privileges the artifact's smallest task-relevant units, records the relations among those units, and requires each higher-order claim to traverse a visible warrant chain from exact marks through local patterns to a bounded reading. It then reintroduces context, rival interpretations, and practical purpose so microscopic attention does not become isolated formalism or overreading.

core_intuition: A paraphrase is useful only after the evidence-bearing grain has had a chance to resist it. Small choices can be load-bearing: a modal verb can change an obligation, punctuation can alter scope, placement can change emphasis, repeated diction can establish a motif, and an omission can make a policy exception consequential. Close reading makes those choices inspectable before they are flattened into a convenient whole.

canonical_formula: warranted_reading = bounded_context × Σ(mark_evidence × formal_relation × recurrence_or_contrast × positional_weight) − unsupported_scale_jumps; paraphrase is admitted only after grain coverage and counterreading checks.

structural_problem: A text or text-like artifact carries consequential meaning through fine-grained form, but readers move too quickly from the artifact to a summary, intention, category, or policy conclusion. The compression erases evidence-bearing detail and hides the inferential jumps between small marks and large claims. Conversely, a reader may fixate on an isolated mark and overread it without testing recurrence, relation, whole-text coherence, or plausible alternatives. The system needs a disciplined mode that preserves grain without losing bounded interpretation.

trigger_conditions: Exact wording, punctuation, syntax, sequence, typography, motif, citation, exception, or omission could materially change the interpretation.

trigger_conditions: A higher-order claim is being made from a compact artifact, yet the path from cited unit to claim is not visible or reproducible.

trigger_conditions: Competing readings agree on the general topic but disagree about what particular words, relations, or formal choices license.

trigger_conditions: The stakes of interpretation justify slower inspection: rights, duties, safety, doctrine, public meaning, historical claims, design behavior, or institutional commitments may turn on textual grain.

trigger_conditions: Paraphrase, search snippets, machine summaries, extracted quotations, or inherited glosses risk substituting for examination of the source artifact.

trigger_conditions: The artifact is short enough, segmentable enough, or selectively bounded enough that task-relevant grain can be inspected without pretending to exhaust an unbounded corpus.

symptoms: Readers offer confident summaries but cannot point to exact passages or marks.

symptoms: A single quotation is detached from its syntactic, sequential, or genre context.

symptoms: Disagreement repeatedly returns because participants use different editions, segment boundaries, translations, or unit definitions without noticing.

symptoms: Formal choices are dismissed as ornamental even though changing them changes uptake.

symptoms: A conclusion depends on one vivid word while contrary recurrence, qualification, or omission elsewhere in the artifact is ignored.

symptoms: Automated extraction or paraphrase smooths ambiguity, modality, hedging, exception structure, or speaker distinction into a falsely determinate claim.

symptoms: Readers oscillate between free association and sterile literalism.

root_tension: Meaning emerges from both local marks and larger contexts. Moving upward too soon destroys evidence-bearing detail; staying local too long mistakes accumulation of observations for interpretation. The archetype must slow abstraction enough for the artifact to constrain the reading, then reconnect the inspected grain to context, whole, rival readings, and use.

anti_signatures: The primary task is to recover a formal grammar tree or machine-readable structure under explicit production rules; grammar_guided_structure_recovery is closer.

anti_signatures: The primary task is to reconstruct period norms, available knowledge, and options around an actor or event; historical_contextualization is closer, though close reading may support it.

anti_signatures: The primary task is to establish provenance, admissibility, or inferential weight for observations that are not chiefly textual marks; evidentiary_trace_warranting is closer.

anti_signatures: The primary task is collective coordination under unfolding uncertainty rather than artifact-grain interpretation; structured_sensemaking is closer.

anti_signatures: The reader merely annotates, highlights, summarizes, or searches a document without building and testing an evidence-to-meaning warrant chain.

anti_signatures: The artifact's exact form is not material to the decision, and a validated summary or ordinary contextual interpretation is sufficient.

structural_intervention: Establish a temporary high-resolution interpretive mode: fix the artifact and version, define a task-relevant grain ladder, defer global paraphrase, inventory formal features and relations, trace exact marks, build micro-to-macro warrant chains, test counterreadings and overreading risk, and only then reintegrate context and produce a bounded interpretation with an explicit stopping rule.

action_logic: Freeze the substrate by recording edition, version, translation, boundaries, locators, and any material formatting that could affect the reading.

action_logic: State the interpretive question and define which kinds of meaning are in scope: semantic, rhetorical, legal, doctrinal, procedural, functional, or experiential.

action_logic: Set a grain ladder from smallest relevant mark through phrase, sentence, passage, section, and whole, adapting unit names to the artifact.

action_logic: Activate a paraphrase-deferral gate: record provisional summaries but do not let them govern the analysis until task-relevant units have been inspected.

action_logic: Inventory potentially load-bearing features, including diction, modality, grammar, punctuation, sequence, emphasis, repetition, contrast, quotation, speaker, typography, image-text relation, exception, and omission.

action_logic: Map relations among marks—recurrence, variation, echo, opposition, dependency, progression, reversal, framing, nesting, and positional prominence—rather than treating evidence as an unordered list of quotations.

action_logic: Build each interpretive claim upward: exact mark to local observation, local observation to pattern, pattern to higher-order reading, and reading to bounded implication.

action_logic: Search for disconfirming marks, rival pattern explanations, version differences, and plausible counterreadings; downgrade or split claims that cannot survive.

action_logic: Reintroduce relevant context and part-whole iteration, checking whether context illuminates the marks or merely overrides them.

action_logic: Stop when additional grain inspection produces no material change to the scoped claims, unresolved ambiguity is recorded, and a reviewer can reproduce the evidence chain.

decision_rules: Use the smallest unit capable of changing the scoped interpretation; do not descend to smaller marks merely to perform thoroughness.

decision_rules: Treat recurrence and relation as stronger support than an isolated curiosity, unless the artifact's conventions make a single mark dispositive.

decision_rules: Require exact locators for consequential claims and preserve enough surrounding context to assess scope and qualification.

decision_rules: Distinguish absence supported by an explicit expectation from silence that could be accidental, irrelevant, or outside the artifact's purpose.

decision_rules: Separate observation, pattern, interpretation, and implication so disagreement can be located at the right inferential step.

decision_rules: Escalate edition, translation, corruption, or transcription disputes before using tiny textual differences as evidence.

decision_rules: Admit a paraphrase only if it survives a diff against the inspected mark set and retains material modality, exception, ambiguity, and relation.

decision_rules: Prefer a narrower warranted reading over an expansive reading that requires unsupported scale jumps.

target_invariants: The exact substrate and version remain identifiable throughout the analysis.

target_invariants: Every consequential higher-order claim remains traceable through explicit steps to located marks or formally justified absences.

target_invariants: Observation remains distinguishable from interpretation and implication.

target_invariants: Formal relations such as order, scope, recurrence, contrast, and placement are preserved rather than flattened into a bag of words.

target_invariants: Context may constrain and illuminate the reading but may not erase inconvenient marks without an explicit reason.

target_invariants: Rival readings and residual ambiguity remain visible when evidence underdetermines.

target_invariants: The stopping rule prevents both premature closure and performative endlessness.

target_invariants: Quotation and citation practices preserve surrounding qualification and do not manufacture support through selective extraction.

expected_outcomes: More reproducible and contestable interpretations.

expected_outcomes: Fewer paraphrase-driven distortions and unsupported interpretive leaps.

expected_outcomes: Earlier discovery of scope, modality, exception, sequence, and omission effects.

expected_outcomes: Clearer diagnosis of whether disagreement concerns the artifact, the observed pattern, the interpretive framework, or the implication drawn.

expected_outcomes: Better preservation of meaningful ambiguity without relativist collapse.

expected_outcomes: More reliable handoff from textual analysis to legal, policy, design, historical, doctrinal, or operational decisions.

prose_essence:
Textual Close-Reading Mode is a controlled shift in interpretive resolution. It slows the movement from artifact to summary long enough for exact wording, punctuation, syntax, sequence, recurrence, contrast, placement, and omission to constrain the reading. Its governing demand is simple but exacting: a large claim must show how it was built from small, located evidence.

The word “textual” is deliberately broad but not unlimited. The primary substrate is language, yet the mode can also apply to text-like artifacts whose marks and relations are stable enough to cite: a contract layout, an interface screen, a diagram with labels, or a policy form. The mode does not authorize free interpretation of anything whatsoever. It requires a bounded artifact, a defined grain, inspectable marks, and a reproducible path from those marks to meaning.

Close reading is not the refusal of paraphrase. It is the postponement of paraphrase until the artifact has had a chance to resist compression. A good paraphrase arrives after the relevant grain has been inspected and retains the modality, qualification, ambiguity, exception, speaker, and formal relations that matter. A bad paraphrase becomes the answer first and recruits quotations afterward.

prose_when_to_use:
Use this archetype when exact form could change a consequential interpretation. Typical signals include disputes about what a clause obliges, why a passage shifts tone, whether a repeated formula is meaningful, how a design steers action, or whether a summary has erased an exception. The higher the stakes and the more compact the artifact, the stronger the case for a temporary high-resolution reading mode.

It is especially useful when participants agree on topic but disagree on warrant. One person sees an isolated word; another sees a pattern. One reads a modal verb as permission; another reads it as obligation. One treats an omission as purposeful; another calls it accidental. Close reading gives those disagreements a common inspection surface by separating the exact mark, its relation, the inferred pattern, the interpretive claim, and the practical implication.

Do not use close reading merely because a document exists. If the question can be answered from a validated summary and no fine-grained feature could change the outcome, ordinary interpretation is sufficient. If the task is corpus prevalence, formal parsing, source provenance, collective crisis sensemaking, or historical option reconstruction, a neighboring archetype should lead. Close reading may support those tasks without owning them.

prose_structural_problem:
The structural problem is premature scale change. Meaning-bearing material exists at several nested levels, but a reader jumps from a small part to a large conclusion without exposing the intermediate steps. The jump may begin with compression—“this policy is about safety”—or with fixation—“this single word proves hostile intent.” Both failures hide how local features relate to one another and to the whole.

Texts intensify this problem because their evidence is relational. A word takes scope from syntax. A sentence changes force through its position after an exception. A repeated image matters because it recurs with variation. An omission becomes evidence only when a convention or parallel passage creates a justified expectation. A quotation can reverse meaning when speaker, irony, negation, or surrounding qualification is removed. Treating the artifact as a bag of words destroys these relations.

The opposite risk is microscopic endlessness. Once every mark is declared potentially meaningful, the reader can always find another detail, another association, or another contextual frame. The archetype therefore treats grain, question scope, counterreading, and stopping as governing constraints. Its purpose is warranted interpretation, not maximal annotation.

prose_intervention_logic:
Begin by fixing the substrate. Record the version, edition, translation, transcription, rendering, and bounded passage. Preserve lineation, typography, image-text relation, or other form when those features could bear meaning. A reader cannot make precise claims while the object of reading silently changes.

Next state the interpretive question and build a grain ladder. The smallest relevant unit may be punctuation in a regulation, a modal verb in a requirement, a line break in a poem, a label in an interface, or a repeated formula in a canonical text. The largest unit may be a sentence, section, scene, document, or collection. The ladder is task-specific: descending below the smallest meaning-changing unit adds noise rather than rigor.

Activate the paraphrase-deferral gate. Summaries may be recorded as hypotheses, but they cannot organize the evidence yet. Inventory formal features, then map relations—recurrence, contrast, sequence, nesting, adjacency, reversal, echo, framing, scope, and omission. Convert observations into patterns only when relations support them.

Build the warrant chain explicitly. A located mark supports a local observation; several observations support a pattern; the pattern supports a bounded reading; the reading supports only those implications that survive scope, context, and counterevidence. Then construct the strongest plausible counterreading. Search for marks it explains better and for details the favored reading leaves anomalous.

Finally reintroduce context and stop deliberately. Genre, history, audience, precedent, authorship, institutional purpose, and use can constrain or transform the reading, but they must not simply overwrite resistant marks. Stop when further inspection no longer materially changes the scoped claims, the evidence chain is reproducible, and residual ambiguity is recorded.

prose_key_components:
### Textual Substrate and Version Record

The analysis needs a stable object. Record the authoritative version, translation, amendment state, rendering, and passage boundary. If a claim turns on punctuation or typography, preserve it. If versions differ, the difference is part of the evidence rather than an inconvenient preprocessing issue.

### Interpretive Question and Scope

Close reading is always reading for something. The question may concern obligation, stance, rhetorical movement, doctrinal relation, user action, or operational meaning. A clear question determines which features are potentially material and prevents the reader from treating every discoverable pattern as relevant.

### Grain Ladder and Unit Boundary

The grain ladder specifies how analysis moves from mark to phrase, sentence, passage, section, and whole. This component is load-bearing because close reading is not simply “careful interpretation”; it governs resolution. It also states when a unit is too small to be stable and when a unit is too large to preserve evidence.

### Paraphrase Deferral Gate

This gate keeps inherited glosses, machine summaries, and early impressions provisional. It does not ban synthesis. It sequences synthesis so that a summary must later demonstrate fidelity to the inspected marks and relations.

### Formal Feature Inventory

The inventory records task-relevant diction, modality, syntax, punctuation, voice, speaker, order, repetition, contrast, citation, typography, genre, and form. It should be selective and reasoned. A feature remains in the analysis because it can change the answer to the interpretive question, not because it is available to count.

### Position, Order, and Relation Map

Marks bear meaning through relation. The map records what qualifies what, which passage frames another, where repetition changes, how an exception nests, and what is foregrounded by placement. It protects the analysis from quotation lists that preserve words but lose structure.

### Recurrence, Contrast, and Omission Register

Recurrence can establish pattern; variation can establish movement; contrast can make categories visible. Omission is more delicate. The register requires a reason the missing element should have appeared—parallel structure, genre convention, defined enumeration, or repeated practice—before silence counts as evidence.

### Exact-Mark Evidence Trace

Every material observation receives a stable locator and enough surrounding context for review. The trace preserves speaker, scope, qualification, and relation. It prevents a precise-looking citation from laundering a decontextualized fragment.

### Micro-to-Macro Warrant Chain

This is the archetype's central integrator. It separates mark, observation, pattern, reading, and implication. A reviewer can accept one layer and reject the next, which turns interpretive dispute from a clash of conclusions into a diagnosable difference about evidence or inference.

### Counterreading and Overreading Test

The favored reading is challenged with contrary marks, conventional alternatives, simpler pattern explanations, and version differences. The goal is not forced balance. It is to learn whether the reading explains more of the artifact with fewer unsupported assumptions than its strongest rival.

### Context Reentry Frame

After grain inspection, the analysis reintroduces genre, period, audience, institution, precedent, authorship, and use. The sequence matters. Context now encounters a visible artifact-grounded reading rather than silently deciding in advance what every mark must mean.

### Interpretive Saturation and Stop Rule

The stop rule asks whether another pass changes any scoped claim, reveals an unexamined material feature, or resolves a recorded uncertainty. When additional detail is merely cumulative, the analysis can close while retaining an ambiguity ledger and excluded-scope note.

prose_common_mechanisms:
### Line-by-Line Annotation Protocol

A structured pass records exact marks, observations, questions, and provisional implications without collapsing them. The protocol is strongest on bounded passages and weakest when it becomes unselective commentary.

### Close-Reading Table

A table separates locator, mark, feature, relation, observation, interpretation, counterevidence, and confidence. The columns force inferential transitions into view. The table is a mechanism, not the archetype: it can be completed mechanically without achieving a warranted reading.

### Diction, Syntax, and Punctuation Trace

This trace follows lexical choice, grammatical attachment, modality, negation, punctuation, and scope. It is essential when small formal differences change duty, agency, temporality, or certainty.

### Motif Concordance and Recurrence Map

A concordance locates repeated terms or forms; the recurrence map adds relation, variation, and function. Frequency alone does not establish importance. The mechanism becomes interpretive when it explains how repetition changes across positions and contexts.

### Sequence and Placement Map

This artifact shows order, framing, adjacency, nesting, progression, and reversal. It helps explain why the same sentence or image would mean differently if placed elsewhere.

### Omission and Negative-Evidence Audit

The audit documents the expectation that makes absence meaningful and tests alternative explanations. It is particularly valuable for enumerations, parallel clauses, repeated formulae, omitted voices, and silently unaddressed edge cases.

### Micro-to-Macro Claim Matrix

For each consequential claim, the matrix lists marks, observations, relations, pattern, scope, defeaters, context, and implication. It is useful in legal, policy, safety, and scholarly settings where reviewers need to reproduce the path.

### Parallel-Passage Comparison

Comparable passages reveal stable convention and meaningful variation. They can test whether a word is exceptional, a formula is routine, or an omission is truly surprising.

### Edition or Variant Collation Table

Collation aligns versions, translations, amendments, witnesses, or renderings. It prevents a reading from presenting version-contingent wording as a stable property of the artifact.

### Paraphrase-Difference Test

The final summary is compared with the evidence map. Reviewers look for lost modality, exception, speaker, ambiguity, sequence, and relation. Material losses require a revised paraphrase or an explicit compression note.

### Counterreading Stress Review

A reviewer constructs the strongest alternative rather than a straw position. The favored reading must explain resistant marks or narrow itself. This mechanism is particularly useful when interpretation will authorize institutional action.

### Interpretive Saturation Log and Contextual Reentry Memo

The saturation log shows whether successive passes still alter the scoped claims. The context memo records how genre, history, audience, authority, and use affect the mark-grounded reading. Together they prevent both endless formalism and context-free closure.

prose_failure_modes:
### Premature paraphrase capture

An inherited gloss, executive summary, search result, or model output becomes the controlling frame. Evidence is then selected to decorate it. Mitigate by marking all early summaries provisional and requiring a post-inspection paraphrase-difference test.

### Isolated-mark overreading

A vivid word, comma, or silence receives more weight than recurrence, relation, genre, or contrary evidence permits. Mitigate with parallel comparison, justified-expectation tests for omission, and the strongest plausible counterreading.

### Unsupported scale jump

A local feature is used to infer broad authorial intent, culture, doctrine, policy purpose, or institutional psychology. The micro-to-macro matrix should expose missing intermediate warrants and force a narrower claim.

### Context erasure and context override

Formalism can treat the artifact as self-contained; contextualism can force every mark to serve an external theory. The context-reentry frame requires both sides to state how mark and context constrain one another.

### Version instability

A claim depends on wording absent from another authoritative edition or translation. Freeze and collate versions, then qualify or withdraw claims that are not stable.

### Feature inventory without reading

The output becomes an impressive catalogue of diction, syntax, images, or interface details. Require each retained feature to support a relation, pattern, scoped interpretation, or explicitly rejected hypothesis.

### Selective quotation

Supporting fragments are cited while qualifications, contrary recurrence, speaker changes, or scope are hidden. Use citation context windows, negative-case search, and independent claim-level review.

### Interpretive endlessness

Every new detail becomes grounds for another pass. Define material-change criteria, a saturation threshold, unresolved-item ledger, and deadline before starting.

### Authority laundering

Technical interpretive language disguises a conclusion determined by power, doctrine, or preference. Separate textual observation, interpretive warrant, authority rule, and final decision so each can be reviewed.

prose_neighbor_distinctions:
**Context-Bounded Meaning Recovery** is the broad parent: it selects frameworks, anchors context, traces evidence, compares readings, and establishes admissible boundaries across many substrates. **Textual Close-Reading Mode** makes resolution governance, paraphrase deferral, formal relation, grain coverage, and micro-to-macro warranting mandatory. Making those obligations universal would overload ordinary interpretation.

**Hermeneutic Iteration** centers recursive movement between part and whole until coherence is adequate. Close reading often uses this loop, but it begins with a different design problem: preserving and exhausting task-relevant artifact grain before compression. Hermeneutic iteration can interpret events or practices without text; close reading can complete a bounded evidence pass without prolonged convergence.

**Grammar-Guided Structure Recovery** reconstructs formal hierarchy under explicit rules. Close reading may use a parse, but asks what syntax, placement, and form warrant as meaning. A valid syntax tree is not yet an interpretation.

**Evidentiary Trace Warranting** governs how observations support hypotheses or claims across evidence types. Close reading specializes the upstream work of identifying textual evidence and formal relation. It can feed an evidentiary warrant system without duplicating its provenance and inferential-weight governance.

**Historical Contextualization** reconstructs period norms, knowledge, constraints, and available options. Close reading inspects source grain; historical contextualization tells the reader how period context changes the significance of that grain.

**Narrative Construction Audit** examines event selection, causal sequence, focal actors, themes, and omissions. Close reading can support it but is equally applicable to nonnarrative clauses, specifications, poems, and interfaces.

**Form-Content Congruence Design** changes a carrier so form better supports intended content. Close reading diagnoses how an existing form bears meaning. **Pragmatic Context Alignment** seeks successful situated uptake; close reading can analyze pragmatic cues without owning communication repair.

prose_cross_domain_examples:
### Literature

A critic examining a poem records pronoun shifts, repeated threshold imagery, syntactic interruption, and the placement of the final sentence. The reading about withdrawal from collective voice is accepted only after those local features form a coherent pattern and survive a counterreading based on genre convention.

### Law and regulation

A statutory duty depends on a modal verb, a defined term, punctuation, and an exception cross-reference. Counsel maps the relations, compares parallel formulations elsewhere, and states which part of the legal conclusion comes from text and which part requires precedent or authorized interpretive doctrine.

### Religious and canonical study

A doctrinal claim is tested against repeated formulae, speaker changes, parallel passages, translation choices, and textual variants. The output records where the artifact supports one reading, where tradition supplies an authority rule, and where uncertainty remains.

### Policy and contracts

A policy summary says a benefit applies universally, but close reading reveals a scope qualifier, an excluded category, and a definition that changes across versions. The final implementation note preserves those distinctions rather than copying the summary.

### Safety and software specifications

Engineers trace “shall,” “should,” “unless,” precedence language, examples, and silent edge cases. The micro-to-macro matrix connects each reading to a test case and identifies requirements whose textual ambiguity needs authorized clarification.

### Interface and design critique

A consent screen's wording, label order, default selection, visual grouping, and missing exit route are inspected as a bounded multimodal artifact. Close reading supports a claim about how the screen frames assent, while user research and consent-governance archetypes remain necessary to establish actual effect and legitimacy.

prose_non_examples:
A chapter summary with several quotations is not close reading if the summary controlled evidence selection. A keyword frequency chart is not close reading without local function, relation, and counterevidence. A syntax tree is not close reading unless it participates in a bounded meaning claim.

Historical context alone is not close reading, though it may constrain it. A stakeholder workshop creating shared interpretation under uncertainty is structured sensemaking. A provenance system authenticating a document is evidentiary or traceability infrastructure. A design revision that aligns a label with intended meaning is sign-meaning alignment.

Nor is every slow reading a close reading. Repeatedly rereading without a question, grain rule, evidence trace, warrant chain, counterreading, or stop condition may deepen familiarity but does not instantiate the archetype.

prose_tradeoffs:
Close reading trades speed for resolution. It requires attention, version control, domain competence, and review time. Those costs are justified when fine-grained form can change a consequential interpretation; they become waste when the artifact's grain is immaterial to the task.

The method also trades apparent simplicity for accountable complexity. A clean summary may become qualified, and an apparently obvious rule may reveal ambiguity. That can improve decisions, but it can also delay action or invite strategic dispute. A stopping rule and decision-authority boundary are therefore as important as detailed analysis.

Tool assistance expands coverage but creates provenance risk. Search, concordance, parsing, and language models can locate patterns or variants, yet they can silently normalize punctuation, omit passages, collapse speakers, or invent synthesis. Assisted work must preserve artifact links and expose selection criteria.

Finally, formal attention can privilege those trained in dominant textual traditions. Domain competence should increase accountability, not close participation. Where texts affect communities or contested traditions, pair technical analysis with appropriate standpoint, translation, consent, and authority safeguards.

prose_invariants_to_preserve:
The exact substrate must remain identifiable. If an edition, translation, or rendering changes, the analysis must show whether its claims survive. Stable citation is not administrative detail; it is part of the evidentiary contract.

Every consequential claim must remain traceable through distinct inferential layers. Observations are not yet patterns; patterns are not yet interpretations; interpretations are not yet legal, moral, historical, or operational conclusions. The chain may be compact, but it cannot be skipped.

Formal relation must survive extraction. Order, negation, scope, qualification, speaker, recurrence, and placement cannot be discarded while the remaining words are presented as faithful evidence.

Ambiguity must not be erased merely because a decision prefers clarity. When the artifact underdetermines, the output should rank or preserve readings and identify which external authority or decision rule resolves the action.

Close reading must remain bounded by context and competence. Exact marks do not eliminate the need for linguistic, legal, historical, community, or technical expertise. Nor does expertise eliminate the obligation to show how the artifact supports the reading.

prose_target_outcomes:
The primary outcome is a reading that can be inspected, challenged, revised, and handed off. A reviewer should be able to locate the same marks, see the same formal relations, identify the point of inferential disagreement, and understand the scope of the conclusion.

Secondary outcomes include fewer summary-induced errors, better detection of exceptions and modalities, improved preservation of ambiguity, and clearer separation between textual evidence and institutional authority. In operational settings, the archetype also improves translation from documents to requirements, test cases, policies, and decisions by exposing which details those translations depend on.

Success is not unanimity. Two readers may still disagree because they weight context differently, accept different conventions, or draw different implications. The archetype succeeds when that disagreement is no longer hidden inside competing paraphrases.

prose_parameter_dimensions:
- **Grain depth:** character, punctuation, word, phrase, sentence, passage, section, whole, or multimodal mark. Descend only as far as a smaller unit can change the scoped reading.
- **Coverage breadth:** exhaustive for a short clause, sampled but justified for a long work, or targeted around a disputed pattern.
- **Paraphrase latency:** how long synthesis remains provisional before grain coverage is adequate.
- **Locator precision:** page, line, clause, timestamp, screen state, version hash, or image coordinate.
- **Relation density:** how many recurrence, contrast, scope, sequence, and positional links must be mapped.
- **Context-entry timing:** minimal context before inspection, staged context during analysis, or full context after the first mark-grounded pass.
- **Counterreading intensity:** self-check, peer challenge, independent reviewer, or adversarial red team.
- **Version sensitivity:** negligible, monitored, collated, or dispositive.
- **Ambiguity tolerance:** resolve, rank, preserve, defer, or escalate.
- **Claim stakes:** exploratory, scholarly, doctrinal, contractual, rights-affecting, operational, or safety-critical.
- **Saturation threshold:** no new marks, no material claim changes, stable counterreading result, or deadline-bounded sufficiency.
- **Tool assistance:** manual, search-supported, corpus-assisted, parser-assisted, or model-assisted, with all automated outputs traceable to the artifact.

Tuning should be proportional. A two-sentence safety requirement may justify exhaustive punctuation and scope analysis. A long novel may require a declared sample of passages plus a recurrence map. Rigor comes from making those choices visible, not from pretending every artifact receives total inspection.

prose_variants_and_near_names:
**Literary and Formal Close Reading** emphasizes diction, voice, rhythm, imagery, recurrence, and aesthetic form. **Legal Textual Close Reading** adds authority, precedent, defined-term, exception, and consequence constraints. **Canonical and Scriptural Close Reading** adds translation, textual witness, parallel passage, canon, and community authority. **Policy, Contract, and Specification Close Reading** links exact terms and relations to implementation duties and test cases.

**Multimodal Artifact-Grain Reading** remains a candidate variant. Interface screens, diagrams, exhibitions, and visual communication can support close reading when their marks and relations are stable enough to cite. It should not become permission for unconstrained interpretation of any designed object.

Names such as **Evidence-Bound Close Reading**, **Fine-Grained Textual Interpretation**, and **Mark-to-Meaning Analysis** point to this archetype. **Line-by-Line Commentary** and **Text Annotation** are mechanisms or practices, not aliases in every case. **Textual Analysis** is too broad: it also includes corpus, computational, thematic, linguistic, and historical methods with different structures.

raw_bundle_path: solution_archetypes/_Batches2/Second Sweep Candidate Batch 01/textual_close_reading_mode_solution_archetype_output_bundle.zip

Literary and Formal Close Reading

short_definition: Reads diction, syntax, image, voice, rhythm, sequence, repetition, and form as interacting evidence for a bounded literary interpretation.

distinctive_feature: Gives unusually high weight to patterned formal relation and aesthetic effect.

distinct_from_parent: Narrows the general close-reading structure to literary or rhetorical form.

still_same_parent_because: It uses the same grain ladder, paraphrase gate, mark trace, warrant chain, and counterreading tests.

use_when: Formal pattern and local variation materially constrain the reading.

use_when: Summary would erase how the artifact produces its effect.

domain: poetry

example: Line breaks, pronoun shifts, recurring images, and syntax are traced before a claim about changing address or stance is accepted.

Legal Textual Close Reading

short_definition: Traces defined terms, modality, punctuation, scope, exceptions, placement, and cross-reference before stating a bounded legal or regulatory reading.

distinctive_feature: Adds authority, precedent, edition, and consequence constraints to mark-level reading.

distinct_from_parent: Narrows the close-reading structure to authoritative rule texts.

still_same_parent_because: Exact-mark tracing and micro-to-macro warranting remain the core intervention.

source_primes: close_reading interpretation order

use_when: Rights, duties, authority, or exceptions may turn on exact textual relation.

use_when: Competing readings can be tested against a shared authoritative text.

example_domains: law regulation contracts

domain: regulation

example: A reviewer maps a qualifier across the operative clause and its exception before defining the regulated class.

Canonical and Scriptural Close Reading

short_definition: Examines wording, formula, parallel passage, translation, textual witness, and canonical placement before advancing a doctrinal or traditional reading.

distinctive_feature: Gives special weight to witness, translation, canon, and interpretive authority.

distinct_from_parent: Narrows the general close-reading structure to canonical traditions.

still_same_parent_because: The same grain, collation, warrant, counterreading, and context-reentry logic applies.

use_when: Translation or textual variants may materially affect the interpretation.

use_when: Parallel passages and canonical position are load-bearing evidence.

example: A doctrinal claim is tested against the wording, speaker, parallel passage, translation choice, and manuscript variation that support it.

name: Policy, Contract, and Specification Close Reading

short_definition: Reads definitions, modal terms, conditions, exceptions, precedence, examples, and silent cases as an auditable basis for implementation.

distinctive_feature: Connects textual grain directly to operational obligations and test cases.

distinct_from_parent: Narrows close reading to implementation-bearing institutional artifacts.

still_same_parent_because: It retains the same mark-to-pattern-to-reading sequence and stopping rule.

source_primes: close_reading evidence order

use_when: Small textual differences can change operational behavior or allocation.

use_when: Implementers need a reproducible evidence chain for the chosen reading.

example: Modal terms, exception clauses, and precedence words are mapped to test cases before implementation.

Multimodal Artifact-Grain Reading

short_definition: Extends grain-bound reading to artifacts where text, image, typography, spacing, sequence, interaction, or material form jointly bear meaning.

distinctive_feature: The evidence grain is multimodal rather than primarily linguistic.

distinct_from_parent: Extends the textual parent while retaining exact-mark and relation accountability.

still_same_parent_because: The same paraphrase-deferral, grain-ladder, warrant-chain, and counterreading obligations remain intact.

use_when: The artifact has stable locatable marks beyond words.

use_when: Formal relations can support reproducible interpretations.

example: Label wording, visual hierarchy, default state, spatial grouping, and omitted escape routes are read together as a bounded artifact.

near_names:
Evidence-Bound Close Reading
Fine-Grained Textual Interpretation
Mark-to-Meaning Analysis
Line-by-Line Commentary


Texture as Signal Encoding

type: archetype

source: generated

batch: Second Iteration/Batch 07

aliases:
Texture Coding
Surface Texture Cueing
Textural Information Encoding
Texture-Based Status Encoding
Tactile and Visual Texture Cueing
Surface Pattern Signal Design
Texture-as-Meaning Mapping

slug: texture

slug: iconicity

slug: iconography

slug: contrast

slug: emphasis

slug: classification

slug: observability

slug: signaling

slug: redundancy

slug: attention

slug: interface

slug: schema

slug: chunking

slug: interoperability

slug: constraint

slug: threshold

slug: dimension

slug: compression

slug: minimalism

components:
Encoded Property Definition
Texture Code Vocabulary
Modality Context Fit
Perceptual Discriminability Check
Legend or Learning Path
Redundancy Mapping
Noise and Clutter Budget
Accessibility and Safety Constraint
Production Consistency Control
Cultural or Domain Convention Register
Texture Intensity Scale
Tactile Calibration Panel
Uncertainty or Quality Mapping
Misleading Texture Guard

mechanisms:
Hatching Pattern Legend
Textured Chart Fill
Data-Quality Texture Overlay
Tactile Paving Surface
Raised Ridge or Bump Marker
Material Finish Code
Haptic Feedback Pattern
Semantic Texture Palette
Texture Sample Card
Redundancy Style Guide

essence_one_line: Use texture as a deliberate code so users can perceive status, category, quality, or affordance without relying only on words, color, or shape.

compression_statement: This archetype treats fine-grained surface variation as an information channel. It defines what property the texture should encode, builds a texture vocabulary with stable meanings, checks perceptual discriminability in the actual modality and context, pairs texture with legends or redundant cues when needed, and controls production consistency so the code survives printing, screens, touch, wear, and scale changes.

core_intuition: Texture sits at the boundary between perception and meaning. A surface can feel rough, look hatched, appear grainy, or pulse with haptic texture before a user reads a label. When that surface variation is assigned a stable meaning and tested for recognizability, it becomes a signal.

canonical_formula: Texture code T: texture vocabulary -> encoded property set P, valid only when discriminability, context fit, redundancy, and production consistency hold for the intended users.

structural_problem: A system needs to communicate status, property, quality, category, warning, or affordance, but ordinary labels, color, shape, position, or icons are insufficient, overloaded, inaccessible, too slow, or unreliable across viewing and handling conditions.

trigger_conditions: Users must parse information quickly without reading lengthy labels.

trigger_conditions: Color is unavailable, semantically overloaded, inaccessible to some users, or likely to be lost in printing or low-light conditions.

trigger_conditions: The information must be available through touch, material finish, or haptic interaction rather than sight alone.

trigger_conditions: A display or object needs to encode a secondary property such as uncertainty, provisional status, quality, hazard, grip, or handling constraint.

trigger_conditions: The same code must survive across media such as screen, print, physical product, packaging, and assistive contexts.

trigger_conditions: Fine-grained differences already exist in the surface, but users are interpreting them inconsistently or accidentally.

symptoms: Users confuse categories that differ only by color or small text labels.

symptoms: A printed, grayscale, low-resolution, or low-light version loses crucial status information.

symptoms: Tactile or material surfaces imply use zones, quality, or safety states without any explicit mapping.

symptoms: Visual texture is decorative in one context and meaningful in another, causing interpretation drift.

symptoms: Data displays hide uncertainty, missingness, or quality differences because there is no secondary cue channel.

symptoms: Texture fills, hatching, or tactile markings are too similar to distinguish under real conditions.

symptoms: Users notice a surface difference but cannot tell whether it is noise, style, wear, or an intended signal.

root_tension: Texture is perceptually salient but semantically under-specified. It can add a resilient channel of meaning, yet it can also become clutter, decoration, false affordance, or inaccessible code unless the mapping from surface variation to meaning is explicitly designed and tested.

anti_signatures: The surface variation is purely aesthetic and not intended to carry information; Aesthetic Coherence System is closer.

anti_signatures: The main decision is whether to use an icon, index, or arbitrary symbol rather than a texture code; Sign-Type Selection is closer.

anti_signatures: The main problem is choosing among representational media broadly rather than designing texture meanings; Representation Fit Selection is closer.

anti_signatures: The texture is only a decorative style token with no encoded status, property, quality, or affordance.

anti_signatures: The main problem is drawing attention to one element, not encoding distinct meanings through surface variation; Focal Emphasis Design is closer.

anti_signatures: The main problem is instrumentation that exposes hidden state, while the display channel is incidental; Observability Instrumentation is closer.

structural_intervention: Design texture as a controlled signal: define the property to encode, create a small texture vocabulary, map textures to meanings, test distinguishability and accessibility in context, pair with redundant cues and legends when needed, and govern reproduction so texture remains meaningful.

action_logic: Identify the specific property, state, category, warning, quality, or affordance that requires texture encoding.

action_logic: Decide whether texture should be primary, redundant, secondary, or confirmatory relative to color, shape, position, icon, label, or sound.

action_logic: Choose the relevant modality: visual pattern, tactile surface, material finish, haptic feedback, or multimodal combination.

action_logic: Build a minimal texture vocabulary with clear differences in density, direction, roughness, grain, ridges, stipple, smoothness, or vibration texture.

action_logic: Map each texture to one meaning and avoid many-to-one or one-to-many assignments unless deliberately layered and documented.

action_logic: Test discriminability with target users under realistic size, lighting, resolution, movement, touch, wear, attention, and assistive conditions.

action_logic: Provide a legend, repeated pairing, standard, onboarding cue, or environmental reference so the texture code can be learned and audited.

action_logic: Add redundant cues when stakes, accessibility, or modality failure make texture alone too fragile.

action_logic: Specify production and maintenance rules so the same texture remains stable across screens, print, manufactured surfaces, cleaning, wear, and versions.

decision_rules: Use texture when another channel is overloaded, inaccessible, unstable, or too slow for the task.

decision_rules: Prefer a small vocabulary when users must recognize texture quickly or at small scale.

decision_rules: Use texture redundantly rather than alone when misinterpretation would be high-cost or safety-sensitive.

decision_rules: Use tactile texture when users need eyes-free, low-visibility, or accessibility-supported interpretation.

decision_rules: Use texture to encode secondary information such as uncertainty or quality only if it does not obscure the primary value.

decision_rules: Reject a texture mapping when target users cannot reliably distinguish it under realistic conditions.

decision_rules: Document any cultural, professional, or standards-based texture convention that users may already bring to the surface.

target_invariants: Every texture has an explicit intended meaning.

target_invariants: Users can distinguish the textures in the actual context of use.

target_invariants: Texture does not contradict color, shape, icon, label, or physical affordance cues.

target_invariants: High-stakes texture cues are redundant, learnable, and tested with target users.

target_invariants: The code remains stable across reproduction media, scale, wear, and maintenance conditions.

target_invariants: Decorative texture is separated from semantically meaningful texture.

target_invariants: The texture vocabulary is small enough to avoid clutter and cognitive overload.

expected_outcomes: Information remains legible when color, text, or shape alone would fail.

expected_outcomes: Users parse status, category, quality, warning, or affordance more quickly and reliably.

expected_outcomes: Data displays, interfaces, and objects become more robust across accessibility, print, lighting, and modality constraints.

expected_outcomes: Texture stops drifting between decoration and meaning because the mapping is explicit.

expected_outcomes: Secondary information such as uncertainty or missingness becomes visible without displacing the primary signal.

expected_outcomes: Material and tactile surfaces communicate intended use or caution with fewer accidental interpretations.

prose_essence:
**Texture as Signal Encoding** uses fine-grained surface variation as an information channel. The surface may be visual, tactile, material, or haptic: hatching in a chart, stipple on a map, ridges on a control, roughness on a grip zone, or vibration texture in a device. The important move is not adding texture for style. It is assigning texture a stable meaning, testing that users can distinguish it, and preserving that meaning across media and conditions.

Texture is useful when ordinary channels are too fragile. Color may be unavailable, inaccessible, overloaded, or lost in printing. Labels may be too slow or too small. Icons may be ambiguous. A surface that users already see or touch can carry status, category, uncertainty, warning, quality, or affordance if the code is deliberate.

prose_tradeoffs: Texture adds redundancy and accessibility, but it can add clutter. Subtle textures preserve visual calm but can fail in practice. Strong textures are easy to detect but may dominate the display. Tactile cues support eyes-free use but require durability, hygiene, safety, and standards attention. Texture can communicate uncertainty, but if it is too dense it can obscure the primary value.

Visual Texture Status Coding

short_definition: A visual variant that uses hatching, stipple, grain, density, or fill pattern to encode categorical status or state.

distinctive_feature: Fine-grained visual surface variation carries the code rather than hue, text, position, or shape alone.

distinct_from_parent: The parent covers texture across visual, tactile, material, and multimodal encodings; this variant centers on visual pattern fills and surface grain.

still_same_parent_because: It uses the same texture vocabulary, discriminability, legend, redundancy, and production-consistency logic.

source_primes: texture representation classification

use_when: Color alone is unavailable, unreliable, inaccessible, or overloaded.

use_when: Users must distinguish categories quickly in a chart, map, label, dashboard, or interface.

use_when: The encoded status remains meaningful when printed, viewed in grayscale, or seen under poor lighting.

example_domains:
data visualization
cartography
operations dashboards
technical diagrams

domain: cartography

example: Different land-use classes are shown with distinct texture fills so a printed grayscale map remains legible.

failure_modes:
textures too similar at small scale
visual clutter obscures the data
legend omitted or inconsistent

Tactile Texture Accessibility Cueing

short_definition: A tactile variant that uses raised, recessed, rough, smooth, ridged, or patterned surfaces to encode information through touch.

distinctive_feature: Texture becomes a tactile information channel rather than merely a visual pattern or aesthetic treatment.

distinct_from_parent: The parent also includes visual and material-signaling texture; this variant centers on touch-based interpretation.

still_same_parent_because: It still solves information encoding through controlled fine-grained surface variation.

use_when: Users may not be able to rely on sight, color, or labels.

use_when: The action environment requires eyes-free or low-visibility interpretation.

use_when: The code can be learned, felt reliably, and distinguished under realistic use conditions.

example_domains:
accessibility design
industrial controls
transit infrastructure
consumer electronics

domain: transit

example: A platform edge uses a standardized tactile texture to warn of boundary and direction.

failure_modes: users confuse alert textures with decoration

failure_modes: the tactile code is inaccessible to the intended users

Material Finish Property Signaling

short_definition: A material-design variant that uses surface finish to signal grip, fragility, heat, quality, direction, wear, or handling constraints.

distinctive_feature: The texture is attached to a physical material interface and often communicates by felt or seen affordance.

distinct_from_parent: The parent includes abstract data and visual encodings; this variant is anchored in physical surface finish.

still_same_parent_because: It uses texture as a controlled code for interpreting property, status, or allowed action.

source_primes: texture signaling interface

use_when: A physical object should communicate how it may be used or handled without relying entirely on labels.

use_when: Surface finish can be manufactured consistently and remains meaningful after wear.

use_when: The texture cue aligns with the actual material property or action affordance it suggests.

example_domains:
product design
manufacturing
packaging
medical devices

domain: industrial design

example: A grip area is knurled while a non-grip surface remains smooth so use zones are recognizable by touch.

failure_modes: a decorative finish implies a false property

Data-Quality Texture Patterning

short_definition: A data-display variant that uses texture overlays or fills to encode uncertainty, missingness, provisional status, or quality class.

distinctive_feature: Texture conveys meta-information about evidence quality rather than the primary measured value.

distinct_from_parent: The parent covers any texture-encoded property; this variant is about confidence, missingness, and reliability signals.

still_same_parent_because: It still encodes information through a controlled texture vocabulary.

use_when: Users need to see not only values but also reliability, provenance, or uncertainty.

use_when: The uncertainty cue must remain visible without replacing the primary data encoding.

use_when: Color, opacity, or text labels are insufficient or already assigned to other meanings.

example_domains:
scientific visualization
operations dashboards
public reporting
risk communication

domain: public dashboard

example: A dotted overlay marks provisional data so users do not treat it as final.

failure_modes: uncertainty texture looks like a data category

failure_modes: users infer false precision from decorative texture

name: Redundant Texture Code with Color or Shape

short_definition: A redundancy variant that pairs texture with color, shape, icon, or label so information survives modality loss or viewing constraints.

distinctive_feature: Texture is deliberately redundant with another representational cue rather than acting alone.

distinct_from_parent: The parent can use texture as the primary code; this variant uses texture as a resilience layer.

still_same_parent_because: The key intervention remains texture-based encoding of status, class, or property.

source_primes: texture redundancy contrast

use_when: A single cue channel is unreliable, inaccessible, ambiguous, or overloaded.

use_when: The same information must survive printing, low light, small displays, assistive technologies, or color-vision differences.

use_when: Users need both fast perceptual parsing and confirmation through another cue.

example_domains:
safety labeling
charts and maps
interface design
industrial controls

domain: safety label

example: A warning state uses both a color and a rough border texture so it remains identifiable without color.

failure_modes: one channel appears to contradict the other

near_names: Accessibility Tactile Feedback Design for Digital Interfaces

near_names: Data Quality Visualization Through Texture Patterns

near_names: Material Property Indication Through Surface Finish


Theory-Responsive Case Sampling Design

batch: Batch 11

canonical_family: Sampling, Inference & Statistical Bias

aliases:
Emergent-Model Case Sampling
Theoretical Sampling Design
Theory-Guided Case Selection
Model-Responsive Case Selection
Saturation-Guided Case Sampling
Grounded Theory Sampling Design
Analytic Case Selection Loop

slug: validation

slug: refinement

slug: feedback

slug: overfitting

slug: uncertainty

slug: evidence

slug: falsifiability

slug: iteration

components:
Emerging Model Frame
Analytic Gap Register
Case Universe and Access Boundary
Case Learning Question
Selection Rationale Record
Case Contrast Palette
Analysis/Sampling Loop
Model Revision Register
Negative or Deviant Case Trigger
Conceptual Saturation Criterion
Scope and Transferability Note
Ethics and Burden Gate
Rival Explanation Matrix
Field Access Contingency Plan
Sampling Stopping Review Panel
Memo Version History

mechanisms:
Grounded Theory Sampling Memo
Constant Comparison Matrix
Theoretical Gap Matrix
Negative Case Sampling Pass
Maximum Variation Case Round
Boundary Case Probe
Rival Explanation Discriminator
Saturation Review Memo
Case Selection Audit Trail
Transferability Claim Check

essence_one_line: Select the next case because it can sharpen, challenge, extend, or saturate the emerging account—not because it statistically represents a population.

compression_statement: Theory-Responsive Case Sampling Design applies when inquiry is building or refining an explanatory model through cases, episodes, sites, documents, interviews, observations, or events. Instead of fixing a representative sample up front, the process alternates analysis and selection: infer the current model, identify its unresolved concepts, relations, boundary conditions, exceptions, and weak comparisons, choose the next case for its expected learning value, analyze it, revise the model and scope, and stop when new cases mainly confirm already stable categories rather than adding material distinctions.

core_intuition: When the goal is theory construction, the best next case is often not the average case. It may be a contrasting case, a deviant case, a boundary case, an extreme case, a confirming case, a missing-context case, or a case that separates two rival explanations. The archetype turns that adaptive choice into a disciplined loop, so analytic curiosity does not become opportunistic cherry-picking and saturation does not become a premature excuse to stop.

canonical_formula: emerging_model + unresolved_concept_or_relation + case_learning_question + traceable_selection_rationale + analysis_loop + saturation_stop_rule -> scoped_theory_refinement

structural_problem: An inquiry is trying to build or refine an explanatory account from cases, but the next observation is chosen either as if the goal were population representativeness or as an ad hoc interesting example. Fixed representative sampling can miss the contrast, exception, or boundary condition needed for model refinement; opportunistic case selection can create confirmation bias, scope creep, and untraceable narrative fitting. The structural problem is the absence of a disciplined link between the current state of the model, the learning question for the next case, and the stop condition for enough cases.

condition: Theory-building or model-refinement goal

description: The inquiry needs to develop concepts, relations, boundary conditions, process accounts, or causal/explanatory hypotheses rather than estimate a population parameter.

condition: Cases can be selected sequentially

description: The investigator can choose additional cases, interviews, sites, documents, incidents, trials, or observations after some analysis has already occurred.

condition: Current model has unresolved structure

description: The emerging account contains ambiguous categories, rival explanations, unexplored contrasts, weak causal links, or uncertain scope conditions.

condition: Learning value differs across possible cases

description: Some candidate cases would teach more about the account than others because they are contrastive, deviant, boundary-testing, typical, extreme, or strategically comparable.

condition: Representativeness is not the primary criterion

description: The inquiry may still care about bias and scope, but the immediate selection criterion is analytic contribution to model development, not population proportion.

condition: Saturation or diminishing learning can be assessed

description: There is a way to judge when new cases are adding no materially new properties, relations, exceptions, or boundary revisions.

symptom: Cases are collected before analysis catches up

signal: A large sample accumulates, but case choice no longer reflects what the current model needs to learn.

symptom: Interesting-case drift

signal: Cases are chosen because they are vivid, available, prestigious, dramatic, or convenient rather than because they answer a named analytic gap.

symptom: Premature saturation claim

signal: The team says nothing new is being learned while rival cases, negative cases, or boundary cases remain unexamined.

symptom: Representative-sampling confusion

signal: A qualitative or case-based model-building inquiry is judged as failed because it is not population-representative, or it overclaims transfer because representativeness was never designed.

symptom: Confirmation spiral

signal: Each new case is chosen because it fits the existing story, making the model more fluent but less tested.

symptom: Untraceable selection logic

signal: Later readers cannot tell why this case was added, what it was expected to test, or how it changed the model.

symptom: Scope creep by anecdote

signal: The account expands to cover every new case without recording which boundary conditions have actually been revised.

root_tension: Model-building inquiry needs adaptive selection because the best next case depends on what has already been learned. But adaptivity creates discretion, and discretion can look like or become cherry-picking unless each selection is anchored to the model state, a learning question, and a revision or saturation criterion.

anti_signatures: Use representative_sampling_design when the main requirement is for a sample to stand in for a population or system under a known sampling frame.

anti_signatures: Use deviant_case_analysis when the central task is explaining a case that violates an established pattern, not designing the whole sequential sampling loop.

anti_signatures: Use generalization_validation when the model is already fitted and the main question is whether it performs on new cases outside the original fit.

anti_signatures: Use hypothesis_testing_frame when the structure is a predeclared claim test against a null or default alternative, not open-ended theory construction.

anti_signatures: Do not use this archetype when cases cannot be chosen or sequenced after interim analysis.

structural_intervention: Create a documented, iterative case-selection loop that begins with the current model state, names the analytic gap or rival explanation, chooses the next case for expected learning value, analyzes it against the model, records the resulting model or scope change, and applies a saturation rule before stopping.

action_logic: State the current model, including concepts, relations, process sequence, boundary conditions, open questions, and confidence limits.

action_logic: Identify the next most valuable learning gap: ambiguous category, rival explanation, unexplored contrast, missing mechanism, weak boundary, or possible negative case.

action_logic: Enumerate candidate cases and classify their likely contribution: confirm, contrast, refine, extend, disconfirm, boundary-test, or separate rivals.

action_logic: Select the next case with a written learning question and selection rationale before or at the point of fielding/collection.

action_logic: Analyze the new case against the model using comparison, memoing, process tracing, coding, or other domain-appropriate methods.

action_logic: Record whether the case added a new concept, property, relation, boundary condition, exception, or only confirmation.

action_logic: Revise the model, scope, and future case-selection priorities based on the result.

action_logic: Stop or pause only when strategically varied, negative, boundary, and confirmatory cases add no materially new structure at the needed decision resolution.

rule: Learning-value rule

description: A case is eligible when it can answer a named question about the emerging model better than available alternatives.

rule: Contrast-before-confidence rule

description: Before declaring saturation, the inquiry must check whether plausible contrastive, deviant, boundary, or rival-explanation cases remain unexamined.

rule: Selection-rationale rule

description: Each added case must have a traceable rationale linking it to a model gap or saturation test.

rule: Scope-revision rule

description: When a case does not fit, the model must be revised, scoped, or explicitly left with residual anomaly rather than silently absorbed.

rule: Saturation-resolution rule

description: Saturation is judged at the resolution needed for the inquiry, not as an absolute claim that no case anywhere could ever teach more.

rule: Representativeness-boundary rule

description: Claims must not be framed as population-representative unless a separate representative-sampling design supports that claim.

target_invariants: The next case remains tied to the current model state and an explicit learning question.

target_invariants: Selection discretion remains visible enough to audit for cherry-picking and confirmation bias.

target_invariants: Negative, deviant, contrastive, and boundary cases remain legitimate sources of model change.

target_invariants: The saturation stop rule distinguishes confirmation from new conceptual, relational, process, or boundary information.

target_invariants: Transfer or generalization claims stay scoped to the evidence and sampling logic actually used.

target_invariants: Analysis and selection remain interleaved; neither outruns the other for long.

expected_outcomes: More informative case sequences for qualitative, comparative, diagnostic, and case-based inquiry.

expected_outcomes: Clearer records of why each case was added and what it changed.

expected_outcomes: Better distinction between theory construction, representativeness, and post-hoc anecdote collection.

expected_outcomes: Reduced premature closure and reduced endless sampling by using explicit saturation criteria.

expected_outcomes: Stronger boundary conditions and more honest transferability claims.

Negative-Case Theoretical Sampling

short_definition: Selects cases likely to contradict or force scope revision in the emerging account.

distinctive_feature: Foregrounds disconfirmation within the broader case-selection loop.

distinct_from_parent: The parent includes multiple case roles; this variant makes countercase search the leading selection criterion.

still_same_parent_because: It remains a case-selection move governed by the current model, selection rationale, and saturation logic.

use_when: The current model may be over-confirmed.

use_when: A plausible counterexample class is known but underexamined.

example: After most teams fit a coordination model, researchers select a team whose coordination works despite missing the predicted condition.

failure_modes: Selecting only theatrical exceptions rather than analytically relevant countercases.

Maximum-Variation Theoretical Sampling

variant_type: subtype

short_definition: Selects widely different cases to discover which properties vary and which remain invariant.

distinctive_feature: Uses variation as an analytic probe rather than as a population-representative stratification.

distinct_from_parent: The parent can choose cases by many learning roles; this variant prioritizes range and invariance.

still_same_parent_because: Case choices are still made according to model-learning value and revision impact.

use_when: Important dimensions of variation are known but not yet explored.

example: Researchers choose novice, expert, constrained, and workaround-heavy users to refine a model of adoption friction.

failure_modes: Mistaking maximum variation for statistical coverage.

Boundary-Condition Case Sampling

short_definition: Selects cases at the edge of the model to learn where it stops applying.

distinctive_feature: Treats boundary cases as primary evidence for scope discipline.

distinct_from_parent: The parent can refine any model element; this variant focuses on applicability boundaries.

still_same_parent_because: The same model-responsive loop governs which boundary case comes next.

use_when: The model seems plausible but scope conditions are unclear.

use_when: The inquiry risks overclaiming transferability.

example: A study selects a classroom that barely meets the intervention’s prerequisite conditions to see where the account fails.

failure_modes: Boundary cases become edge-case theater without a model-revision rule.

Confirming Saturation Check Sampling

short_definition: Adds final cases mainly to verify that new data no longer change the model at the required resolution.

distinctive_feature: Uses cases to test the stop condition, not to widen exploration.

distinct_from_parent: The parent includes discovery and refinement; this variant emphasizes closure and diminishing marginal learning.

still_same_parent_because: The stop decision is still based on the same model-change register.

use_when: Stopping would be consequential or contested.

example: A researcher adds two cases from an underchecked subgroup and records that they confirm existing categories without changing properties or relations.

failure_modes: Using confirmation-only cases to conceal lack of contrastive or negative sampling.

near_names:
Theoretical Sampling Design
Grounded Theory Sampling Design
Emergent-Model Case Sampling
Analytic Case Selection Loop