Jul 02, 2026
Protocol for Social Architecture Diagnostics: A Reproducible Workflow for Case Framing, Diagnostic Passport Construction, Evidence Mapping, and Human Review
- Nikolay Kalmykov1
- 1MGIMO University, Doctoral Candidate
- Nikolay Kalmykov: Candidate of Sociological Sciences. ORCID: 0000-0002-9620-9225; Web of Science ResearcherID: P-9384-2017; Scopus Author ID: 57192095141.
- socioarchitectonics
Protocol Citation: Nikolay Kalmykov 2026. Protocol for Social Architecture Diagnostics: A Reproducible Workflow for Case Framing, Diagnostic Passport Construction, Evidence Mapping, and Human Review. protocols.io https://dx.doi.org/10.17504/protocols.io.j8nlk74z1g5r/v1
Manuscript citation:
Kalmykov, N. N. Protocol for Social Architecture Diagnostics: A Reproducible Workflow for Case Framing, Diagnostic Passport Construction, Evidence Mapping, and Human Review. protocols.io, draft v0.1, 2026.
License: This is an open access  protocol distributed under the terms of the  Creative Commons Attribution License,  which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: July 02, 2026
Last Modified: July 02, 2026
Protocol Integer ID: 320225
Keywords: social architecture, social diagnostics, diagnostic passport, case study protocol, evidence matrix, human review, digital governance, public service route, institutional analysis, social environment design, reproducible workflow, applied sociology, socio-technical systems
Disclaimer
This protocol publishes only the external reproducible workflow. It does not disclose proprietary scoring algorithms, production prompts, internal weights, closed heuristics, benchmark cases, raw user materials, credentials, API keys, or confidential data.
Abstract
This protocol describes a reproducible workflow for diagnosing social architectures in organizational, digital, public-service, educational, urban, market, and policy contexts. It guides researchers and practitioners through case boundary setting, input package preparation, source mapping, diagnostic passport construction, layer-by-layer assessment, evidence linking, human review, and reporting. The protocol is intended for structured case analysis, dissertation research, applied diagnostics, and comparative case accumulation. It defines a diagnostic workflow, not a universal validated scale, causal proof procedure, or automated decision-making system. The public version publishes only the external reproducible layer of the method and does not disclose proprietary scoring algorithms, internal weights, production prompts, closed benchmark cases, confidential user data, or platform credentials.
Guidelines
Method Status
This is a diagnostic workflow, not a universal validated measurement scale, causal proof procedure, automated decision-making system, or substitute for legal, medical, financial, HR, political, or administrative judgment. Outputs must be reviewed by a human before use in consequential settings.
Materials
Minimum materials:
- short case description;
- diagnostic object and context;
- practical or research question;
- intended result or decision to support;
- list of key actors and affected groups;
- available rules, procedures, route descriptions, interface screenshots, communication materials, complaints, observations, or public sources;
- source register;
- diagnostic passport template;
- evidence matrix template;
- human review checklist.
Optional materials:
- anonymized user journey notes;
- public statistics;
- institutional documents;
- previous diagnostic reports;
- synthetic demo case;
- expert review comments;
- consent form if real participant data are used.
Do not include personal data, raw confidential files, private system logs, closed scoring rules, production prompts, internal weights, closed benchmark cases, API keys, credentials, or deployment details.
Data Recording
Maintain:
- case registry;
- source register;
- claim register;
- diagnostic passport;
- layer map;
- gap register;
- compensation map;
- evidence matrix;
- correction module register;
- review trail;
- research export log;
- version history.
Recommended version fields:
- protocol version;
- case record version;
- source set version;
- report version;
- reviewer and review date.
Quality Checks
Before finalizing the report, verify:
- the diagnostic object is clear;
- the boundary is explicit;
- every key conclusion has an evidence matrix row;
- facts, interpretations, hypotheses, recommendations, and limitations are separated;
- missing data are visible;
- at least one alternative explanation is recorded for major conclusions;
- no closed algorithm, production prompt, internal weight, API key, personal data, or confidential case material is included;
- the report includes human verification questions;
- recommendations do not exceed the evidence;
- research export is anonymized;
- limitations are stated before public or institutional use.
Minimum quality threshold: the report is acceptable only if a reader can trace each major conclusion back to inputs, source statuses, diagnostic layer, gap type, limitation, and human review question.
Expected Outputs
Primary outputs:
- diagnostic passport;
- social architecture layer map;
- gap/disbalance register;
- evidence matrix;
- compensation map;
- correction module register;
- diagnostic report;
- human review trail.
Optional outputs:
- anonymized research export;
- repeat diagnostic comparison;
- case appendix for dissertation or article;
- synthetic demonstration case;
- expert review form;
- public case summary.
Limitations
This protocol is a diagnostic workflow, not a universal validated measurement scale. It supports structured interpretation, reproducibility, comparison, and human review, but it does not by itself prove causal effects, policy effectiveness, organizational performance, or the success of a redesign.
Main limitations:
- case-based evidence may be incomplete;
- source reliability may vary;
- user descriptions may contain bias or omissions;
- public sources may be outdated or politically framed;
- route reconstruction may miss hidden informal practices;
- diagnostic categories require trained interpretation;
- repeat diagnostics do not prove causality without an appropriate research design;
- scoring and prioritization are not published in this public protocol;
- outputs require human review before use in consequential decisions.
Citation Note
Before DOI assignment, cite this as a draft protocol. After publication, replace the placeholder with the DOI assigned by protocols.io.
Safety warnings
Published reproducible layer:
- case framing;
- input package preparation;
- source registration;
- diagnostic passport construction;
- layer-by-layer assessment;
- gap/disbalance registration;
- evidence matrix construction;
- human review;
- reporting and repeat-diagnostics procedure.
Protected know-how layer:
- proprietary scoring algorithms;
- internal weights;
- production prompts;
- closed heuristic rules;
- benchmark cases;
- raw user materials;
- confidential documents;
- API keys, credentials, and deployment details.
Ethics statement
Apply the following safeguards:
- minimize personal data;
- anonymize participant comments and case records before research use;
- separate operational case materials from research exports;
- do not publish identifiable user stories without consent;
- distinguish user descriptions from verified facts;
- do not infer protected characteristics unless they are explicitly relevant, lawful, and ethically justified;
- do not use the protocol for manipulation, covert profiling, punitive targeting, or automated sanctions;
- do not present diagnostic output as a final legal, medical, financial, HR, political, or administrative decision;
- include a human review step before applying recommendations;
- document limitations and missing data.
If the protocol is used with minors, dependent participants, patients, employees under pressure, or vulnerable groups, obtain separate ethical review and adapt consent procedures.
Before start
1. Define the diagnostic object in one sentence.
2. Define the main practical or research question.
3. Set the case boundary: organization, service, route, platform, policy, market, territory, educational program, communication system, or another bounded social environment.
4. Define the analysis level: individual route, group interaction, organization, platform, territory, institutional field, or cross-level case.
5. Select one primary diagnostic mode, such as research case, service dropout, complaint diagnostics, career route, audience communication, project premortem, comparison of options, technology impact, reform program, due diligence, market entry, urban route, or educational program.
6. Create a case ID.
7. Create a source register.
8. Decide whether open-source search is allowed.
9. Decide whether anonymized research export is allowed.
10. Confirm the public disclosure boundary.
Minimum start condition: the protocol can begin when the researcher has a diagnostic object, a problem statement, an intended result, and at least one source or observation.
Core Workflow
Step 1. Register the Case
Create a case record with case ID, date, researcher or team, diagnostic mode, object of analysis, context or territory, analysis period, public/private status, and research export status.
Output: case registration entry.
Step 2. Define the Diagnostic Question
Write one main question and up to three secondary questions. Clarify what is not working, for whom, at which route step or institutional layer, and what decision the diagnosis should support.
Output: diagnostic question block.
Step 3. Set the Boundary of the Social Architecture
Describe what is inside and outside the case: actors, affected groups, route or process, rules, procedures, digital systems, interfaces, feedback channels, appeal channels, statuses, rights, obligations, sanctions, incentives, included sources, and excluded sources.
Output: boundary note.
Step 4. Build the Input Package
Collect and register input materials. For each source, record source ID, title or description, source type, origin, date or version, reliability level, relevance level, access status, and whether it can be cited publicly.
Output: source register.
Step 5. Classify Input Claims
Extract or summarize claims from the materials. Label each claim as fact, user description, source statement, interpretation, hypothesis, recommendation, or limitation. Do not merge these statuses.
Output: claim register.
Step 6. Construct the Diagnostic Passport
Fill the diagnostic passport with case ID, domain, analysis level, diagnostic mode, object and boundary, key actors, affected groups, route or process, formal rules, informal norms, digital tools, automated or semi-automated decisions, feedback channels, appeal or restoration mechanisms, trust and legitimacy indicators, known barriers, known compensatory mechanisms, missing data, and output boundary.
Output: diagnostic passport v0.1.
Step 7. Map the Diagnostic Layers
Assess the case across four layers:
1. Institutional layer: formal rules, rights, obligations, accountability, authority, sanctions.
2. Spatial-organizational layer: route, access points, sequence of actions, service path, organizational handoffs.
3. Normative-semiotic layer: meanings, trust, perceived fairness, role expectations, signals, communication, status recognition.
4. Digital layer: platforms, interfaces, automated decisions, data visibility, algorithmic opacity, human override, digital exclusion.
For each layer, record observed elements, evidence, gaps or contradictions, affected groups, missing data, and human verification questions.
Output: layer map.
Step 8. Identify Gaps and Disbalances
Identify points where the social architecture does not connect properly. Typical gap types include unclear entry point, rule-practice mismatch, rule-interface mismatch, opaque decision, missing responsible actor, missing feedback, missing appeal, non-restorable status loss, excessive route burden, digital exclusion, informal workaround dependency, symbolic promise without operational route, KPI or metric substitution, and conflicting actor incentives.
For each gap, record gap ID, description, affected layer, affected group, evidence, claim status, confidence level, what may weaken the conclusion, and what must be checked by a human reviewer.
Output: gap register.
Step 9. Map Compensatory Mechanisms
Identify how the system continues to function despite gaps. Examples include personal contacts, manual intervention, informal mediation, repeated submissions, unofficial instructions, external channels, user self-education, discretionary help by frontline staff, and hidden labor by families, colleagues, or intermediaries.
For each mechanism, record mechanism ID, what gap it compensates, who pays the cost, whether it is stable, fragile, unfair, or invisible, and whether it should be formalized, reduced, or replaced.
Output: compensation map.
Step 10. Build the Evidence Matrix
Create a matrix linking each key conclusion to its basis. Minimum columns: conclusion ID, conclusion text, claim status, source IDs, evidence summary, confidence level, limitation, human verification question, and possible alternative explanation.
Rule: no important conclusion should appear in the report without an evidence matrix row.
Output: evidence matrix.
Step 11. Formulate Diagnostic Hypotheses
Convert the main gaps into testable diagnostic hypotheses.
Recommended form: If [architectural element] is absent, unclear, overloaded, or contradictory, then [actor/group] experiences [barrier, uncertainty, distrust, workaround, dropout, status loss, appeal failure, or reduced agency].
Do not present hypotheses as proven causal effects.
Output: diagnostic hypothesis list.
Step 12. Identify Correction Modules
For each major gap, propose a minimal correction module. Use the format: what route element is corrected; what is changed; how the change can be checked; stopping criterion; possible side effect; data needed before implementation.
Examples include adding a visible appeal channel, clarifying the responsible actor, reducing route steps, separating informational and sanctioning messages, adding human review for contested automated decisions, publishing restoration conditions, creating a status tracker, and replacing an informal workaround with a formal support path.
Output: correction module register.
Step 13. Prepare the Diagnostic Report
Prepare a structured report with title and case metadata, short finding summary, diagnostic passport, layer map, route or process map, gap register, risk and limitation profile, compensation map, evidence matrix, alternative explanations, correction modules, human review checklist, and data/source limitations.
Output: structured diagnostic report.
Step 14. Conduct Human Review
At least one reviewer should check whether the case boundary is correct, sources are represented accurately, facts and interpretations are separated, missing data are visible, conclusions are overstated, recommendations exceed the evidence, confidential or personal data are removed, and protected know-how is not accidentally disclosed.
Possible review actions: approve, reject, edit, needs more data, or mark as out of scope.
Output: review trail.
Step 15. Prepare Anonymized Research Export
If consent and disclosure rules allow, prepare a minimal anonymized research export. Suggested fields: case ID, diagnostic mode, domain, analysis level, dominant layer, gap types, route barriers, appeal presence, restoration presence, feedback presence, digital opacity presence, compensation signs, correction module type, confidence level, missing data, output boundary, and research export consent.
Do not export raw personal data or confidential materials.
Output: anonymized research export.
Step 16. Run Optional Repeat Diagnostics
If a correction module is applied or new evidence appears, repeat the diagnostic workflow. Compare the gap register before/after, route clarity, feedback and appeal visibility, digital opacity, compensation dependency, evidence strength, and human review status.
Do not claim causal effect unless the design supports such inference.
Output: repeat diagnostic comparison.