I found the book heavily discounted so I decided to buy it, mainly because I liked the look of the "Veemeunics" . These are interesting little sentences using these kanji hybrids to link characters in your memory mainly by shape. For instance ‰“istant ‰€arden, in fact a ‰Žonkey's den... And the idea behind using hybrids I find quite interesting. why ‰“istant is different than ‰“ = distant and oddly a more useful connection. I also think the ambiguity at times helps by making me look closer or think harder. I first thought ‰Žonkey might be Donkey because of the potential rhyme. but in fact it's monkey and I think it might now be a permanent memory. or has the potential to be. To be fair to the author he does have this to say. "KanjiHybrids are not an end in itself, but a learning tool to further knowledge. The ultimate goal is familiarity with kanji compounds, pure and simple. You must set in motion a lifetime commitment for advancing your kanji reading and writing skills through constant and continuous application." Indeed if you take away the hybrids, the method is very much a traditional one. The twist is it's using your 16 years plus of English knowledge to give you a leg up. I think it might work and intend to give it a try. Nothing to lose really and it lends itself as an addition to how I already try to learn kanji. The indices are interesting. The index of English key words is the first I've seen in a dictionary. There are also indices based on JLPT level and Japanese grade which could be useful. As well as the usual reading index and radical index. Less useful I find is the kana index. I'm not sure why it is there as the reading index does a better job. Also of limited usefulness, I think, is the new method of indexing kanji -- the flip index. I think this is novelty for novelty's sake. It's meant to be an easy way for non-kanji literate people to find a kanji, but I'm not sure it's precise enough. Or clearly enough explained. Jack Halpern's SKIP method is a more accurate and more thought out method based on shape and definitely better explained.
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