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People are open sourcing their metrics, and building taxonomy. To get the market from niche to mainstream people are working on taxonomy, metrics and peer and trend ratings. The taxonomy of social and environmental terms enables the aggregation of data from different providers and multiple data collection systems. “ .
Additional resources: Digital Skills Framework — a taxonomy of digital skills, plus further learning resources to help build skills in each area, aimed at global nonprofits. Using adult learning principles in technology trainings — an NTEN Digital Inclusion Fellow shares a few key lessons about how to (and how not to) train adults.
We provided a model-based taxonomy that unified many graph learning methods. The clients evaluate these suggestions and return measurements. The World Federation of Advertisers has adopted these algorithms as part of their measurement system. We also had a number of interesting results on graph neural networks (GNN) in 2022.
The taxonomy is rudimentary and not very informative. and elsewhere, and on these social networking sites there is at least the basic evaluation of how many others link to the sites. It's part of helping people to easily adopt RSS readers as an information coping skill. There's not even a description of what the blogs do.
The evaluation of each phase typically relies on comparing a dirty dataset against a clean (ground truth) version, using classification metrics like recall, precision, and F1-score for error detection (see for example Can Foundation Models Wrangle Your Data? Stay tuned then! References Can Foundation Models Wrangle Your Data?
The "taxonomy of archetypes" both allows museums to be judged fairly and appropriately, and allows institutions to grow in their unique abilities, rather than by cobbling together a bit of this and a bit of that, becoming wayward and watered-down. But no one becomes best at one thing by messing with all things.
The evaluation/feedback/training process, which doles out reinforcement and/or curates which data to train on, is almost entirely automated. Some tasks are clearly checkable, others are evaluated by AIs. They attempt to evaluate misalignment via (a) testbeds informed by model organisms and (b) honeypots.
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