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ant-translation-process

Extracts Actor-Network Theory translation phases and identifies controversies from case text.

24|7|Updated Nov 15, 2025
Search Tags:#qualitative analysis#actor-network-theory#translation process#network stabilization#controversy mapping#science and technology studies
One-click install
npx skills add https://github.com/ptreezh/sscisubagent-skills --skill ant-translation-process
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ant-translation-process
Source: https://github.com/ptreezh/sscisubagent-skills/tree/main/skills/ant-translation-process
Command: npx skills add https://github.com/ptreezh/sscisubagent-skills --skill ant-translation-process

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, networkx, matplotlib, seaborn, scipy, jieba, and includes scripts (resource) components.

What problem does it solve?

This Skill helps you understand and reconstruct how, in Actor-Network Theory, different actors’ concerns and interests get transformed into a shared network through translation across key phases, including how failures and controversies affect stabilization.

Core Features & Use Cases

  • Four-phase translation tracing: follow problematization, interessement, enrolment, and mobilization in a step-by-step analysis.
  • Controversy and failure mapping: identify points of resistance, conflict, and breakdown, and connect them to impacts on network formation.
  • Success/stability evaluation: assess translation effectiveness and the degree of network stabilization using extracted chains and metrics.
  • Use cases: analyze technology adoption or governance implementation in Chinese socio-technical contexts; study how alliances form, how roles are bound, and how facts/technologies become “black-boxed” through successful stabilization.

Quick Start

When you provide a case description or text about a network-building process, ask the skill to trace the translation phases, identify controversies or resistance, and output a translation timeline with stabilization assessment.

Frequently Asked Questions about ant-translation-process

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I trace Actor-Network Theory translation phases from qualitative case text?▼

Actor-Network Theory translation phases are traced by extracting problematization, interessement, enrolment, and mobilization events from case text to generate a structured timeline of network construction and stabilization.

What is the best way to map controversies and resistance in socio-technical network analysis?▼

Mapping controversies in socio-technical network analysis involves detecting resistance and breakdown points in case text, then linking these events to their impacts on network formation and stabilization.

Can I evaluate network stabilization and black-boxing using graph metrics?▼

You can evaluate network stabilization by applying optional graph metric computation via NetworkX, using graph structures to assess translation effectiveness and how technologies become black-boxed.

Does this Actor-Network Theory analysis tool work with Chinese socio-technical contexts?▼

The Skill works with Chinese socio-technical contexts by using the Jieba dependency for text processing, specifically analyzing technology adoption and governance implementation in these environments.

How do I construct a translation chain for science and technology studies?▼

Constructing a translation chain for science and technology studies involves phase-focused extraction from case descriptions to bind actors into alliances and map the sequence of network formation events.

What are the limitations of using qualitative analysis for controversy mapping?▼

A limitation of qualitative analysis for controversy mapping is that it requires phase-focused textual extraction, meaning failure detection and stabilization assessment depend entirely on the detail provided in the case text.

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