Reseña del libro "Stumbling Toward Happiness: Haibun and Hybrid Poems (en Inglés)"
Poetic meditations from a journey of self-discovery and transformation. "This book will find you when your soul needs it most. What a beautiful experience! I have loved all of Kat Lehmann's books over the years, but this one struck me as her most profound work yet!" - The Rebecca Review (Vine Voice) ★★★★★Stumbling Toward Happiness celebrates the process of personal growth and the enduring center of joy within. Themes include connectedness and compassion, the gifts of imperfection, radical forgiveness, healing after loss, a return to simple abundance, re-awakening to wonder, and the rediscovery of beauty in our lives. Reminiscent of the reflections of Mark Nepo, Mary Oliver, and Thich Nhat Hanh, Stumbling Toward Happiness will take you on a quest of deep soul-searching. The 111 entries of linked poetry and prose will resonate as you reflect on your own source of inner wisdom and joy.Wishing Shelf Independent Book Award Finalist (2019) Stumbling Toward Happiness includes new poems as well as poems published by esteemed literary journals, including Rattle, Frogpond, Modern Haiku, The Heron's Nest, tinywords, Blithe Spirit, and NHK-Japan Haiku Masters.Notes on the Japanese haibun form, in which the meaning of prose paragraphs is expanded by short haiku and tanka poems, are included in the back of the book.Praise for Stumbling Toward Happiness from Amazon Readers (international): "Uplifting and a guide to help in troubled times. Brilliantly moving, and inclusive, at a time when more of us are suffering in these troubled times." ★★★★★"seduced me into loving poetry" ★★★★★"captures wonderfully the profundity of the everyday processes we all live through" ★★★★★"Kat Lehmann's abilities to express deep feelings of emotion in graceful, insightful language are extraordinary." ★★★★★"I am savoring each deeply touching piece of prose, every sparkling gem of poetry." ★★★★★"Tremendously cathartic." ★★★★★Sample poems can be read using the Amazon "Look Inside" feature.
