Bibliographic record
Abstract
Reviewed by: Badlands: A Geography of Metaphors by Ken Delgarno Michael Farrell Badlands: A Geography of Metaphors. By Ken Delgarno. Foreword by Ross King. Markham on: Red Deer Press, 2014. ix + 194 pp. Illustrations, bibliography. $45.00 paper. It takes an unusual personality to fall in love with badlands and then to spend a lot of time poking around in them. Either one is a romantic at heart, taken by the poetic shapes of eroded landforms and the intense colors of mineral- laced clays, or one is an outlaw on the run looking for an impenetrable secluded place to hide out where nobody in their right mind would try to follow. Ken Delgarno is clearly among the first group. His coffee table book of color photographs made in eleven southern Canadian or northern US Plains locations speaks to an obsessive compulsion to carry camera equipment into fairly inhospitable landscapes and to seek out viewpoints that portray “the most surreal and magical terrain you can imagine.” Badlands are places where the bones of the earth show through. Mostly hot and dry in the good months, home to snakes, antelope, and raptors, badlands are not easy on humans. Formed initially when the last ice age ended as retreating glaciers and rushing water sculpted canyons and valleys, badlands are usually found in semiarid regions that today are subject to the erosional forces of occasional cloudbursts and nearly constant winds. Many of the bizarre formations created by all this erosion are composed of exotic volcanic soils, like bentonite, that make for sparse vegetation, treacherous roads after a rain, and stunning visuals for those willing to take the time and effort to actually get off the road and explore. Ken Delgarno offers us a dozen or more views in each of his chosen Northern Plains locations. Many of his images, taking advantage of modern digital camera technology, make use of “high dynamic range” or nighttime “light painting” techniques. The result is a complex visual portrait of each of these hidden gems. Delgarno visited his locations in a variety of seasons and weather conditions, shooting at night and during the golden hours of sunrise or sunset. Badlands tend to have rich colors that all but disappear during the middle of the day when the sun is high, making the colors become bleached and faded. So he paid his dues to bring home the many striking images that fill this volume. My only complaint is that I wish he had included detailed maps of his chosen locations and their geographic relation to each other. It is obvious that Ken Delgarno’s literary and poetic self also fell in love with these badlands. Each photograph is captioned with a poetic title that he has found in the works of Canadian and American authors. And each chapter includes several pages of text offering personal anecdotes and outlining the location’s history and geography, great stuff like the caves where Butch Cassidy and his gang hid or the location of a wall of rock art that depicts a Blackfoot battle with enemy Plains tribes. In this sense Badlands is also a travelogue or potential visitor’s guide. [End Page 317] Michael Farrell net Television/Agricultural Leadership, Education and Communication University of Nebraska–Lincoln Copyright © 2015 Center for Great Plains Studies, University of Nebraska–Lincoln
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".