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Record W2801787911 · doi:10.1353/mwr.2018.0027

Deep Map Country: Literary Cartography of the Great Plains by Susan Naramore Maher

2018· article· en· W2801787911 on OpenAlexaboutno aff
Matthew S. Luckett

Bibliographic record

VenueMiddle West review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicArchaeology and Natural History
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyHistoryCartographyArt historyArchaeology

Abstract

fetched live from OpenAlex

Reviewed by: Deep Map Country: Literary Cartography of the Great Plains by Susan Naramore Maher Matthew S. Luckett Susan Naramore Maher, Deep Map Country: Literary Cartography of the Great Plains. Lincoln: University of Nebraska Press, 2014. 256 pp. $45. American road trip passengers traversing the Great Plains have surely welcomed the invention of smart phones and seatback DVD players. Long derided as flat and boring, the Plains are too often seen as an unnecessary geographic obstacle to ostensibly more interesting geographic regions to the east and west. Similarly, certainly millions of airline passengers over the past several decades have opened up their airplane windows above Kansas or Nebraska, looked down upon the farms and villages peppering an end-less array of large green and brown squares, and quickly returned to their in-flight magazines. Those travelers are missing out. The region’s flat horizons belie its depths and hidden worlds, tricking visitors into not noticing the biome’s complex ecology, the landscape’s violent geological and historical past, and the land’s stubborn refusal to behave according to colonists’ expectations. Perhaps that is why, according to Susan Naramore Maher, Great Plains writers and scholars have pioneered “deep mapping,” or literary cartography, in their works. Literary cartography seeks to express, explore, accentuate, and add dimensionality to places that often seem blank or empty on maps, and featureless to newcomers. Maher’s study of this genre’s imprint on the region, [End Page 105] Deep Map Country: Literary Cartography on the Great Plains, is an essential synthesis to a body of work that transcends and frequently ignores disciplinary, cultural, and national boundaries. This study is organized thematically, beginning with first chapter introduction based on her 2001 article in Western American Literature that explains the concept of deep-mapping and its regional context. The four chapters that follow are each built around two or three works whose comparisons provide the substance of Maher’s discussion. Wallace Stegner’s Wolf Willow and William Least Heat-Moon’s PrairyErth exemplify efforts to recover deep map histories of the Plains from Saskatchewan to Kansas in Chapter Two. Maher then juxtaposes human settlement against Plains ecology in the third chapter, whose analysis of Don Gayton’s The Wheatgrass Mechanism, John Janovy Jr.’s Dunwoody Pond, and Wes Jackson’s Becoming Native to this Place illustrates their approach from “the edges [of the Plains], sharing the bounty of their research, yet understanding that science, by itself, is not enough to guide communities into settled futures” (28). Chapter Four discusses the work of deep time excavators John McPhee and Loren Eiseley, whose books Rising from the Plains and The Immense Journey, respectively, tell the grand story of the region’s geological past. Finally, Chapter Five investigates the experiential Plains through the works of Julene Bair’s One Degree West, Sharon Butala’s Wild Stone Heart, and Linda Hasselstrom’s Feels Like Far. Many readers may already be familiar with Stegner, McPhee, and other writers featured in Maher’s discussion. But for anyone unfamiliar with literary cartography as a transformative, cumulative literary genre, this book does a vital service. The discursive works surveyed here stand alone, and are in many ways idiosyncratic within their own literary and scientific niches. But as Maher demonstrates these works are in dialogue with one another, and their approaches emanate from a set of common concerns that the Plains are, popularly boring, endlessly fascinating, and existentially threatened by human overuse. These themes all figure prominently in the conclusion, which narrates both the recent resurgence of interest in the Plains among writers and their varied attempts to save Plains communities as they hemorrhage population. While Maher’s monograph is a welcome and necessary introduction to the rhizomatic world of deep mapping and its didactic application to the [End Page 106] Great Plains, maps and illustrations would help the reader better visualize this intricately layered world. This reviewer, a Great Plains scholar and longtime visitor, had no trouble imagining the historical, geological, and cultural layering of small towns and fissures in the earth, but what about the historian in Boston or the English professor in Berkeley? As important as this book is, it should be more accessible...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.523
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.016
GPT teacher head0.270
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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