Virtual Pages - Source Excerpt 63
Summary
This source excerpt preserves a bounded section of 2IA.org/wp-content/themes/twoia-intelligence/inc/virtual-pages.php so readers can inspect the evidence without opening the full source file.
**Source path:** 2IA.org/wp-content/themes/twoia-intelligence/inc/virtual-pages.php
__( 'Use the page to understand what 2IA is claiming to be and what it is refusing to be.', 'two-identities-anonymous' ),
__( 'Use it as a trust check before reading sharper investigations or civil-liberties claims.', 'two-identities-anonymous' ),
__( 'Use it to test whether future pages still serve public accountability, privacy, correction, and human freedom.', 'two-identities-anonymous' ),
),
'review_questions' => array(
__( 'Does this statement of identity match the actual publication workflow?', 'two-identities-anonymous' ),
__( 'Does the page make independence, scope, and public-interest boundaries clear enough to evaluate?', 'two-identities-anonymous' ),
__( 'Does direct language stay tied to records, rights, and correction rather than posture?', 'two-identities-anonymous' ),
),
'publication_boundary' => __( 'About pages should define mission, independence, scope, and standards. They should not imply official authority, secret access, operational capability, or permission to harass, deceive, intrude, or expose private people.', 'two-identities-anonymous' ),
),
'public-records-and-foia' => array(
'context' => __( 'Public-records dossiers turn accountability concerns into requestable record categories. The topic should help readers ask for contracts, policies, budgets, audits, retention schedules, training material, meeting packets, and correction logs through lawful channels.', 'two-identities-anonymous' ),
'evidence' => array(
__( 'Record category, agency or public body, date range, vendor name, office, program, contract number, or meeting context.', 'two-identities-anonymous' ),
__( 'Response history: confirmation numbers, deadlines, extensions, denials, exemptions, releases, appeals, and correction notes.', 'two-identities-anonymous' ),
__( 'Public-interest explanation connecting the requested record to rights, oversight, spending, surveillance, AI, data retention, or redress.', 'two-identities-anonymous' ),
__( 'Publication review that redacts private people and preserves the accountability point.', 'two-identities-anonymous' ),
),
'use' => array(
__( 'Use the dossier to narrow a broad concern into a records request that an office can search and answer.', 'two-identities-anonymous' ),
__( 'Use released records to compare public promises against contracts, policies, budgets, and actual practices.', 'two-identities-anonymous' ),
__( 'Use appeals and correction routes when records are denied, over-redacted, stale, or misleading.', 'two-identities-anonymous' ),
),
'review_questions' => array(
__( 'What exact record category would make this claim more concrete?', 'two-identities-anonymous' ),
__( 'What exemptions, redactions, or missing context need appeal or clarification?', 'two-identities-anonymous' ),
__( 'What can be published without exposing private people in released records?', 'two-identities-anonymous' ),
),
'publication_boundary' => __( 'Records work should inspect accountable institutions, not become harassment, private-person exposure, mass contact, or a way to launder sensitive details into public copy.', 'two-identities-anonymous' ),
),
'false-positives' => array(
'context' => __( 'False-positive dossiers track how errors form, travel, and resist correction. The public value is practical: identify the system, the bad inference, the downstream harm, the appeal path, and the evidence needed to repair the record.', 'two-identities-anonymous' ),
'evidence' => array(
__( 'Error path evidence: flags, labels, scores, copied notes, stale records, vendor feeds, agency systems, platform decisions, or reputation channels.', 'two-identities-anonymous' ),
__( 'Redress evidence: notice, reasons, appeal forms, human review, deletion rules, audit logs, and downstream correction mechanisms.', 'two-identities-anonymous' ),
__( 'Confidence evidence separating confirmed harm, reported allegation, plausible inference, stale data, and unknowns.', 'two-identities-anonymous' ),
__( 'Minimization evidence protecting victims, bystanders, minors, and private people affected by the error.', 'two-identities-anonymous' ),
),
'use' => array(
__( 'Use the dossier to ask where the error originated and how far it traveled.', 'two-identities-anonymous' ),
__( 'Use it to demand correction paths that move through the same systems as the bad record.', 'two-identities-anonymous' ),
__( 'Use it to keep error stories evidence-led and privacy-first.', 'two-identities-anonymous' ),
),
'review_questions' => array(
__( 'What record, score, label, or inference is actually wrong?', 'two-identities-anonymous' ),
__( 'Who can correct it, and who else received the bad version?', 'two-identities-anonymous' ),
__( 'What proof would fix the error without exposing the affected person further?', 'two-identities-anonymous' ),
),
'publication_boundary' => __( 'False-positive pages should not turn affected people into examples for spectacle. Publish the system failure, the evidence class, and the correction need while minimizing personal exposure.', 'two-identities-anonymous' ),
),
'surveillance-systems' => array(
'context' => __( 'Surveillance-system dossiers explain architecture, ownership, data flows, procurement, access rules, retention, audit trails, and redress. The public question is how power is organized and whether that organization is lawful, narrow, auditable, and correctable.', 'two-identities-anonymous' ),
'evidence' => array(
__( 'Contracts, procurement files, privacy impact reviews, data-sharing agreements, vendor documentation, budgets, and renewal records.', 'two-identities-anonymous' ),
__( 'Policy evidence: access rules, authorization standards, audit logs, retention schedules, deletion procedures, sharing limits, and appeal paths.', 'two-identities-anonymous' ),
__( 'Technical-claim evidence stated at governance level: data sources, model claims, integration points, and limitations without operational misuse detail.', 'two-identities-anonymous' ),
__( 'Public-accountability evidence: meeting minutes, oversight reports, inspector-general style findings, litigation records, or public statements.', 'two-identities-anonymous' ),
),
'use' => array(
__( 'Use the dossier to ask who owns the system, what data enters it, who can query it, and how errors are corrected.', 'two-identities-anonymous' ),
__( 'Use procurement and policy records to compare what a system promises against what it can actually do.', 'two-identities-anonymous' ),
__( 'Use minimization and audit questions before repeating technical claims about people.', 'two-identities-anonymous' ),
),
'review_questions' => array(
__( 'What part of the architecture affects rights?', 'two-identities-anonymous' ),
__( 'Which contract, policy, or audit trail proves the claim?', 'two-identities-anonymous' ),
__( 'What information should remain out because it would enable probing, evasion, or targeting?', 'two-identities-anonymous' ),
),
'publication_boundary' => __( 'Surveillance-system pages can discuss governance and public accountability. They must not publish probing instructions, evasion guidance, sensor-triggering paths, or targetable infrastructure detail.', 'two-identities-anonymous' ),
),
'ai-surveillance' => array(
'context' => __( 'AI-surveillance dossiers focus on inference, accountability, provenance, error handling, human review, appeal, and the gap between model confidence and human reality. Automation becomes inspectable without pretending that a score is proof.', 'two-identities-anonymous' ),
'evidence' => array(
__( 'Model-governance evidence: procurement files, model cards, impact assessments, audit results, training-data descriptions, and human-review rules.', 'two-identities-anonymous' ),
__( 'Decision evidence: what the model influences, who owns the final decision, what reasons are given, and how a person can appeal.', 'two-identities-anonymous' ),
__( 'Error evidence: false-positive rates, known bias, stale data, hallucination risk, synthetic-media uncertainty, and correction logs.', 'two-identities-anonymous' ),
__( 'Provenance evidence showing which sources support a claim and where AI assisted the editorial process.', 'two-identities-anonymous' ),
),
'use' => array(
__( 'Use the dossier to separate model output from verified fact.', 'two-identities-anonymous' ),
__( 'Use it to demand human review with authority, not decorative oversight.', 'two-identities-anonymous' ),