FLR
The Fisheries Library in R, a collection of tools for quantitative fisheries science, developed in the R language, that facilitates the construction of bio-economic simulation models of fisheries systems.
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Rijal Al Kashi - Report 176

For students of Islamic seminaries ( hawza ) and Western academics alike, understanding is essential to grasping how early Shia scholars dealt with polarized narrators, political pressure (Taqiyya), and the very definition of "reliability." What is Rijal al-Kashi? (Context is Key) Before dissecting Report 176, one must understand the source. Muhammad ibn Umar al-Kashi was a pioneer. Unlike later scholars (like Najashi or Tusi) who focused on praise ( madh ) or condemnation ( dhamm ), al-Kashi was a collector of reports about narrators . He documented what the earlier Imams (specifically Imams Baqir, Sadiq, Kadhim, and Ridha – peace be upon them) reportedly said about specific individuals.

In the intricate world of Islamic scholarship, particularly within Twelver Shia Islam, the science of ‘Ilm al-Rijal (the study of narrators) is the guardian of authenticity. Without it, the vast ocean of Hadith (prophetic traditions) would be a murky pool of unreliable anecdotes. Among the most seminal texts in this field is Rijal al-Kashi (also known as Ikhtiyar Ma’rifat al-Rijal ), compiled by Abu ‘Amr Muhammad ibn ‘Umar al-Kashi (d. ~340-345 AH) and later abridged by Shaykh al-Tusi. Rijal Al Kashi Report 176

Within this dense compendium of biographical evaluations, one specific entry has sparked centuries of debate, reconciliation attempts, and theological reflection: . For students of Islamic seminaries ( hawza )

In the end, Report 176 remains a testament to the depth of Shia Rijal . It proves that the Imami tradition does not take its texts mechanically; it wrestles with them, allowing contradiction to spark deeper insight rather than superficial rejection. For the serious student of Hadith, that is the ultimate lesson of . Unlike later scholars (like Najashi or Tusi) who

His work is unique because it records "raw data"—statements from the Imams describing a narrator as a "liar," a "forger," a "believer," or a "ghali" (extremist). is one such raw data point. The Specific Text of Rijal Al Kashi Report 176 To analyze the keyword effectively, here is a translation of the famous report (numbered differently in various prints, but standard in the Tusi redaction as #176): "It was narrated from Hisham ibn Salim, from Habib al-Sijistani, that Abu ‘Abdillah (Imam Ja’far al-Sadiq, peace be upon him) said concerning a group of people: 'They are neither believers nor disbelievers... those who doubt (or hesitate) regarding Ali (as).' Then (the Imam) mentioned a people who claimed to follow the Imams but rejected some of their commands. The Imam said: 'They are the worst of creatures... They are the dogs of the people of Hell.'" While the exact translation varies, the core of Report 176 involves Imam al-Sadiq issuing a severe condemnation—comparing a specific deviant group to dogs of Hell —while simultaneously acknowledging that these individuals claim loyalty to the Ahl al-Bayt. Why is Report 176 So Controversial? At first glance, this seems like a standard condemnation of enemies. However, the controversy arises from whom the report is traditionally applied to .

Installing FLR

To install the latest versions of any FLR package, and all the necessary dependencies, start R and enter

install.packages(repos=c(FLR="https://flr.r-universe.dev", CRAN="https://cloud.r-project.org"))

A good starting point to explore FLR is A quick introduction to FLR

About FLR

The FLR project has been developing and providing fishery scientists with a powerful and flexible platform for quantitative fisheries science based on the R statistical language. The guiding principles of FLR are openness, through community involvement and the open source ethos, flexibility, through a design that does not constraint the user to a given paradigm, and extendibility, by the provision of tools that are ready to be personalized and adapted. The main aim is to generalize the use of good quality, open source, flexible software in all areas of quantitative fisheries research and management advice.

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