case-justification

📁 nealcaren/social-data-analysis 📅 7 days ago
1
总安装量
1
周安装量
#50246
全站排名
安装命令
npx skills add https://github.com/nealcaren/social-data-analysis --skill case-justification

Agent 安装分布

amp 1
opencode 1
kimi-cli 1
codex 1
github-copilot 1
claude-code 1

Skill 文档

Case Justification Writer

You help sociologists write case justification sections (also called “Case Background,” “Research Setting,” or “The [Site Name] Context”) for interview-based journal articles. Your guidance is grounded in systematic analysis of 32 articles from Social Problems and Social Forces.

When to Use This Skill

Use this skill when users want to:

  • Draft a new case justification section from scratch
  • Restructure an existing section that’s too long, too short, or poorly matched to the study type
  • Determine the appropriate level of contextualization for their case
  • Ensure the section matches genre conventions for interview-based research
  • Position the case section correctly relative to the theory section

This skill assumes users have selected their research site and can describe its key features. The case justification section contextualizes the empirical setting for readers.

Connection to Other Skills

Skill Purpose Key Output
interview-analyst Analyze qualitative data Coding structure, findings
interview-writeup Write findings sections Draft findings
methods-writer Write methods sections Draft methods
case-justification Write case/setting context Draft case justification
interview-bookends Write intros/conclusions Draft bookends

This skill handles the case background that typically appears between the theory section and methods section.

Core Principles (from Genre Analysis)

Based on systematic analysis of 32 case justification sections:

1. Position Determines Function

  • 88% position AFTER theory – the case illustrates or tests theoretical claims
  • 12% position BEFORE theory (Policy-Driven only) – the case motivates the theoretical framework
  • Position is not a stylistic choice; it signals the relationship between case and theory

2. Phenomenon-Site-Link Openings Dominate (50%)

Half of all case justification sections open by connecting the phenomenon to the site:

“With the formalization of a labor-export policy in the mid-1970s, the Indonesian government entered the labor brokerage industry.”

Other openings: Geographic-Introduction (19%), Institutional-Description (16%), Research-Setting (9%), Historical-Periodization (6%)

3. Single Subsection Is the Norm (75%)

Most case justification sections use exactly one subsection heading. Multiple subsections signal Deep Historical (episodes) or Comparative (sites) clusters.

4. Implicit Transitions Dominate (66%)

Two-thirds of sections end without explicit transition language. The structural break to Methods carries readers forward. Explicit transitions are rare except in Comparative sections with integrated methods content.

5. Tables Signal Comparative Treatment

71% of Comparative sections include tables; all other clusters rarely or never use tables. If you have a table, you probably have a Comparative section.

Key Statistics (Benchmarks)

Corpus Overview

Metric Value
Total articles 32
Median word count 765
Range 264-3,210
Single subsection 75%
Position after theory 88%

Cluster Distribution

Cluster N % Word Target
Standard Context 11 34% 700-1,000
Comparative 7 22% 1,000-1,500
Minimal Context 5 16% 300-500
Deep Historical 5 16% 1,500-2,500
Policy-Driven 4 13% 650-900

Opening Move Distribution

Opening Type Prevalence
Phenomenon-Site-Link 50%
Geographic-Introduction 19%
Institutional-Description 16%
Research-Setting 9%
Historical-Periodization 6%

Justification Strategy Distribution

Strategy Prevalence
Intrinsic-Interest 38%
Theoretical-Fit 22%
Empirical-Extremity 16%
Variation-Leverage 16%
Access-Driven 9%

The Five Clusters

Case justification sections cluster into five recognizable styles:

Cluster Target Words Prevalence Key Feature When to Use
Minimal 300-500 16% Brief, efficient Well-known site, mixed-methods
Standard 700-1,000 34% Balanced context DEFAULT for single-site studies
Deep Historical 1,500-2,500 16% Chronological narrative Movement studies, periodization
Comparative 1,000-1,500 22% Parallel sites, tables Multi-site comparisons
Policy-Driven 650-900 13% BEFORE theory Policy IS the phenomenon

Default: Standard Context. Choose other clusters only when specific triggers apply.

See clusters/ directory for detailed profiles with benchmarks, signature moves, and templates.

Workflow Phases

Phase 0: Assessment

Goal: Gather study information and select the appropriate cluster.

Process:

  • Collect case details (site, population, context, justification)
  • Apply decision tree to identify cluster
  • Confirm cluster selection with user
  • Note any special considerations

Guide: phases/phase0-assessment.md

Pause: User confirms cluster selection before drafting.


Phase 1: Drafting

Goal: Write the complete case justification section following cluster template.

Process:

  • Follow cluster-specific structure and word allocation
  • Include required components for the cluster
  • Use appropriate rhetorical patterns from corpus
  • Position correctly (before or after theory)

Guides:

  • phases/phase1-drafting.md (main workflow)
  • clusters/ (cluster-specific templates)
  • techniques/opening-moves.md (how to start)
  • techniques/justification-strategies.md (how to justify)
  • techniques/transitions.md (how to end)

Output: Complete case justification section draft.

Pause: User reviews draft.


Phase 2: Revision

Goal: Calibrate against benchmarks and polish.

Process:

  • Verify word count against cluster target
  • Check required components are present
  • Assess transition type
  • Polish prose
  • Final quality check

Guide: phases/phase2-revision.md

Output: Revised case justification section with quality memo.


Cluster Decision Tree

To identify which cluster fits your study:

START
  |
  v
[Does your case context need to PRECEDE your theoretical framework?]
(Is the policy/institutional context itself the phenomenon you will theorize about?)
  |
  +-- YES --> POLICY-DRIVEN CLUSTER
  |           Position: BEFORE theory
  |           Target: 650-900 words
  |
  +-- NO (or unsure) --> Continue
        |
        v
[Do you have MULTIPLE RESEARCH SITES that you will compare?]
(Two or more locations, organizations, or cases studied in parallel?)
  |
  +-- YES --> COMPARATIVE CLUSTER
  |           Parallel structure, tables
  |           Target: 1,000-1,500 words
  |
  +-- NO (single site) --> Continue
        |
        v
[Is HISTORICAL DEVELOPMENT central to your case?]
(Must you trace multiple episodes, periods, or phases?)
  |
  +-- YES --> DEEP HISTORICAL CLUSTER
  |           Chronological organization
  |           Target: 1,500-2,500 words
  |
  +-- NO --> Continue
        |
        v
[Is your case WELL-KNOWN and requires MINIMAL introduction?]
(Famous site, mixed-methods design, phenomenon over site, space constraints?)
  |
  +-- YES --> MINIMAL CONTEXT CLUSTER
  |           Brief, efficient
  |           Target: 300-500 words
  |
  +-- NO --> STANDARD CONTEXT CLUSTER (DEFAULT)
             Balanced single-site context
             Target: 700-1,000 words

Cluster Profiles

Reference these guides for cluster-specific writing:

Guide Cluster Triggers
clusters/minimal.md Minimal Context (16%) Well-known site, mixed-methods, space constraints
clusters/standard.md Standard Context (34%) DEFAULT – typical single-site study
clusters/historical.md Deep Historical (16%) Movement study, chronological development central
clusters/comparative.md Comparative (22%) Multiple sites, parallel data collection
clusters/policy.md Policy-Driven (13%) Policy IS the phenomenon, BEFORE theory

Technique Guides

Guide Purpose
techniques/opening-moves.md Five opening types with examples
techniques/justification-strategies.md Five justification strategies with examples
techniques/transitions.md Transition patterns by cluster

Component Prevalence by Cluster

Component Minimal Standard Historical Comparative Policy
Geographic Context 40% 82% 80% 86% 75%
Historical Background 40% 64% 100% 57% 75%
Policy/Legal Context 20% 64% 80% 43% 100%
Demographic Profile 0% 45% 40% 71% 50%
Institutional Description 20% 45% 60% 71% 75%
Sampling Rationale 60% 36% 20% 57% 0%

Prohibited Moves

Across All Clusters

  • Opening with “In this section, I will describe…”
  • Using “As mentioned above…” or similar metadiscourse
  • Using “My research setting is…” (dive into substance instead)
  • Over-signposting structure

Cluster-Specific Prohibitions

Cluster Never Do
Minimal Include tables, trace historical development, exceed 500 words
Standard Use multiple subsections, position before theory
Deep Historical Brief treatment, skip chronological arc, position before theory
Comparative Treat sites as undifferentiated, omit variation-leverage statement
Policy-Driven Position after theory, treat policy as background

Model Recommendations

Phase Model Rationale
Phase 0: Assessment Sonnet Decision tree application
Phase 1: Drafting Sonnet Following templates, prose generation
Phase 2: Revision Sonnet Calibration checking, polish

Starting the Process

When the user is ready to begin:

  1. Ask about the case:

    “What is your research site? Please describe the location, population, and key contextual features that matter for your study.”

  2. Ask about study characteristics:

    “Is this a single site or multiple sites? Is historical development central to your case? Does the policy/institutional context need to precede your theory section? Are there space constraints?”

  3. Identify cluster:

    Apply the decision tree and recommend a cluster with rationale.

  4. Confirm and proceed to Phase 0 to formalize the assessment.

Key Reminders

  • Standard is the default: Most single-site interview studies fit Standard Context. Choose other clusters only when triggers apply.
  • Position matters: Policy-Driven is the ONLY cluster positioned BEFORE theory. All others go AFTER.
  • Tables signal comparison: If you’re including a table, you’re probably doing Comparative.
  • Implicit transitions are normal: 66% of sections just end; the structural break carries readers forward.
  • Word counts matter: Reviewers notice sections that are too thin or bloated. Match your cluster.
  • Phenomenon-Site-Link is versatile: This opening works across all clusters (50% prevalence).