Remm Model
Paula Shuffleburg
In the sociological model, individuals are viewed as the product of their cultural environment. Humans are not evaluators any more than ants, bees, and termites are evaluators. They are conventional and conformist, and their behavior is determined by the taboos, customs, mores, and traditions of the society in which they were born and raised. In this model individuals are also often viewed as social victims, a concept that has gained widespread acceptance in many quarters. (See Sykes, 1992).
By contrast, REMM is an evaluator. The REMM model recognizes that customs and mores serve as important constraints on human behavior, and that individuals who violate them incur costs in many forms. But REMMs compare the consequences of alternative courses of action, including those that involve the flouting of social norms, and consciously choose actions that lead to their preferred outcome. Moreover, if the costs or benefits of alternative courses of action change, REMMs change their behavior. In the sociological model, individuals do not.
Ok, so why is it such a problem that Jensen and Meckling have such a distorted view of sociology, and ignore the importance of culture in determining preferences and such? Because it informs the policies they prescribe for society:
There is a U.S. health care problem, to be sure; but it does not stem from too little regulation and too few subsidies. Rather it comes from our third-party insurance system that effectively removes responsibility for the costs from the most important decisionmaker, that is, the patient. The key to solving this problem is to impose the financial consequences of their medical decisions on patients through greater use of co-pay insurance with larger deductibles that place first dollar costs on patients while protecting them against catastrophic illness.
As regards to human nature, after 6 years of studying psychology (and given my new found career in philosophy of science (since you gave the task of specifying what people are to philosophers)) I can tell you definitively a few things regarding their nature:
Behaviourism served as a useful model in psychology for some years and lead to some very effective therapies (and some pretty terrible ones). However, it fell not because it contained patently false assumptions (like inner mental life is inconsequential), but because (amongst other reasons) it was shown to be an inadequate account of certain phenomena (e.g. language), ceased to be considered a fruitful paradigm for further research and because it was augmented by a paradigm that served the psychological community better for understanding human behaviour (namely cognitive behaviourism).
The question is how much this is true (how much of our nature is, for instance, shaped by evolutionary factors rather than cultural ones) and how much say (freedom) do we have in determining our own lives.
Implements TRACDS (Temporal Relationships between Clusters for Data Streams), a generalization of Extensible Markov Model (EMM). TRACDS adds a temporal or order model to data stream clustering by superimposing a dynamically adapting Markov Chain. Also provides an implementation of EMM (TRACDS on top of tNN data stream clustering). Development of this package was supported in part by NSF IIS-0948893 and R21HG005912 from the National Human Genome Research Institute. Hahsler and Dunham (2010) .
Since 2000, WFRC has partnered with our Mountainland Association of Governments (MAG) to develop and support a shared, regionwide travel demand model called the Wasatch Front Travel Demand Model (WF-TDM).
The WF-TDM is a modified 4-step travel model that incorporates a travel time feedback loop in order to evaluate roadway congestion costs in its distribution of trip origins and destinations and its travel mode choice modules. The model calculates roadway volumes, travel speed indicators, transit route boardings, and regional statistics including vehicle miles traveled (VMT), vehicle hours traveled (VHT), transit/auto/non-motorized mode shares, and trip length costs.
These household and job distribution projections inform future trip generation in the regional TDM. And in turn, REMM factors travel accessibility derived from the travel model into its predictions of land development activity.
WFRC and MAG hosted a expert peer review of REMM and its related processes in August 2019. Three land use modelers from comparable MPOs (Albuquerque, Detroit, Phoenix) were provided with REMM 1.0 documentation in advance of a 2 day in-person review seminar that featured presentations from and discussion among the panelists and WFRC/MAG area stakeholder agencies. The review concluded that REMM is well within best practices for land use modeling and recommended potential future areas of enhancement (view 2019 REMM Peer Review report).
WFRC is also an affiliate of the State Data Center network established by the US Census Bureau and closely coordinates with other data providers, including the Kem C. Gardner Policy Institute at the University of Utah, US Census Bureau, and Utah Department of Workforce Services.
WFRC employs sophisticated transportation and land use modeling tools to provide decision-makers, agency staff, and the public with reliable, insightful forecasts from which to analyze future scenarios and best inform planning for our Region.
As transportation and land use are mutually dependent, forecasting for both of these systems must work in tandem in order to optimally support the development, selection, and prioritization of future transportation projects to meet future needs. Similarly, the integrated WFRC/MAG modeling tools can be critical for exploring local land use policies such as those that promote urban and local centers, and the impact of our urban systems on air quality.
WFRC Analytics often has the opportunity to present information regarding our models and forecasting tools at conferences or meetings. Past presentations serve as an excellent resource into how our modelling and forecasting tools assist in planning efforts. Below are some of the meaningful presentations our team has presented within the last few years. Many of the presentations were presented at in forums like the Utah Model Users (UtahMUG) or the Utah Data Engineers and Scientist in Transportation (uDEST). Many more presentations were given at conferences like those held by the Institute of Transportation Engineers (ITE), Utah Tranportation Conference (UTC), the Association of Metropolitan Planning Organizations (AMPO), and others. In addition, some presentations that were given at colleges or within house at WFRC itself are also listed.
The Wasatch Front TDM and REMM are updated every four years in sync with the four-year RTP cycle. These models serve the Salt Lake City-West Valley City, Ogden-Layton, and Provo-Orem Urbanized Areas. For more information on any of the above, contact the WFRC Analytics Group.
GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. GGUF offers numerous advantages over GGML, such as better tokenisation, and support for special tokens. It is also supports metadata, and is designed to be extensible.
As this model is based on Llama 2, it is also subject to the Meta Llama 2 license terms, and the license files for that are additionally included. It should therefore be considered as being claimed to be licensed under both licenses. I contacted Hugging Face for clarification on dual licensing but they do not yet have an official position. Should this change, or should Meta provide any feedback on this situation, I will update this section accordingly.
Note for manual downloaders: You almost never want to clone the entire repo! Multiple different quantisation formats are provided, and most users only want to pick and download a single file.
I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.
This thesis addresses the modeling approach to benefit the riparian zone nutrient management related to water quality in the Northeast and Midwest of USA. Nutrient (primarily Nitrogen (N)) loss from agricultural watersheds through runoff and drainage water continues to be a water quality concern of global importance. Since N is a crucial input for the sustainability of agriculture, the use of N has increased dramatically in recent decades and the excessive nutrient losses have increased too. Like global concern, agriculture (cropland, pasture, managed forest) is an important component of many watersheds of the USA Northeast where N flux to major estuaries is of substantial concern. In this circumstance, the finding from almost 30 years of research on riparian zone hydrology and biogeochemistry demonstrates that riparian zones can serve as best management practices (BMPs) to minimize the adverse agricultural impact on water quality.
c80f0f1006