Summary of your 'study carrel' ============================== This is a summary of your Distant Reader 'study carrel'. The Distant Reader harvested & cached your content into a collection/corpus. It then applied sets of natural language processing and text mining against the collection. The results of this process was reduced to a database file -- a 'study carrel'. The study carrel can then be queried, thus bringing light specific characteristics for your collection. These characteristics can help you summarize the collection as well as enumerate things you might want to investigate more closely. This report is a terse narrative report, and when processing is complete you will be linked to a more complete narrative report. Eric Lease Morgan Number of items in the collection; 'How big is my corpus?' ---------------------------------------------------------- 7 Average length of all items measured in words; "More or less, how big is each item?" ------------------------------------------------------------------------------------ 2135 Average readability score of all items (0 = difficult; 100 = easy) ------------------------------------------------------------------ 94 Top 50 statistically significant keywords; "What is my collection about?" ------------------------------------------------------------------------- 2 illustration 2 Sammy 2 Paddy 2 Lightfoot 2 Green 2 Forest 1 wolf 1 track 1 Yan 1 Wilson 1 Valley 1 Thornton 1 Ted 1 Tammie 1 Starr 1 Stag 1 Smoky 1 Robinson 1 Rabbit 1 Pythias 1 Nimble 1 Mr. 1 Minnesota 1 Mech 1 March 1 Mahela 1 Lorton 1 Loring 1 John 1 Jimmy 1 January 1 Figure 1 February 1 Crestwood 1 Boody 1 Blade Top 50 lemmatized nouns; "What is discussed?" --------------------------------------------- 667 wolf 565 hunter 562 deer 362 time 332 day 199 snow 194 man 182 way 177 pack 173 eye 171 foot 165 tree 162 area 157 place 154 one 152 thing 148 head 147 season 147 kill 146 illustration 140 mile 138 night 136 buck 135 track 131 antler 130 trail 129 year 121 stranger 121 animal 108 something 107 pond 107 camp 103 hunting 101 mother 101 game 98 wood 95 nothing 95 anything 93 side 93 people 92 study 90 gun 90 age 88 water 87 minute 86 thicket 83 winter 83 dog 79 week 77 condition Top 50 proper nouns; "What are the names of persons or places?" -------------------------------------------------------------- 827 Lightfoot 660 Ted 643 _ 268 Nimble 261 Al 246 Forest 236 Green 199 Sammy 197 Mr. 180 Tammie 157 Deer 154 Paddy 113 Mrs. 109 Peter 107 Rabbit 107 Jimmy 101 Mahela 100 L. 94 Thornton 93 Mech 89 Jay 89 D. 88 Quack 88 February 86 John 81 Minnesota 78 Yan 76 River 75 Smoky 72 Big 71 Wilson 71 Beaver 68 Robinson 64 Coon 63 Loring 63 Figure 60 Reddy 59 wolf 54 Fox 52 Crow 52 Blade 51 Mountain 51 Callahan 49 Lorton 49 . 47 Pythias 47 Cuffy 46 Bear 44 al 43 Valley Top 50 personal pronouns nouns; "To whom are things referred?" ------------------------------------------------------------- 3450 he 1720 it 1374 i 1126 you 929 him 892 they 440 them 298 she 242 we 230 me 144 himself 106 her 31 us 25 ''s 22 itself 20 myself 19 yourself 18 themselves 18 one 12 ''em 9 herself 7 his 6 yours 4 theirs 3 ourselves 2 ya 2 ours 2 huh 2 em 1 yan 1 him--"you 1 hers Top 50 lemmatized verbs; "What do things do?" --------------------------------------------- 5835 be 2466 have 1154 do 652 know 600 see 492 go 478 say 478 come 395 get 372 find 305 take 286 make 267 think 267 look 253 tell 213 kill 210 want 181 run 180 follow 171 seem 159 leave 157 hunt 135 hear 133 shoot 131 watch 129 feel 123 stand 118 begin 117 grow 116 give 115 keep 113 wait 111 stop 110 turn 108 try 107 ask 105 mean 102 let 94 bring 91 hide 91 catch 90 move 88 start 88 eat 84 put 80 become 76 drive 75 sit 75 fall 74 show Top 50 lemmatized adjectives and adverbs; "How are things described?" --------------------------------------------------------------------- 1567 not 489 so 391 then 355 up 349 more 310 out 299 little 296 just 277 back 276 now 271 long 254 only 253 very 246 other 220 as 213 there 213 good 207 away 206 down 187 old 184 even 183 still 183 big 176 right 174 much 171 all 170 never 170 great 156 here 155 again 149 well 145 too 143 first 130 once 125 last 116 at 114 same 107 enough 106 over 106 few 106 far 103 in 103 ever 102 sure 102 always 102 almost 101 terrible 99 most 99 beautiful 97 also Top 50 lemmatized superlative adjectives; "How are things described to the extreme?" ------------------------------------------------------------------------- 69 good 61 least 54 most 15 great 12 near 11 Most 10 big 9 slight 9 high 7 long 7 large 7 fine 7 faint 5 old 5 bad 4 happy 3 strong 3 close 2 wise 2 small 2 shy 2 handsome 2 clever 2 bright 1 young 1 tight 1 thick 1 swift 1 sporty 1 southw 1 short 1 pure 1 plain 1 odd 1 mere 1 low 1 lofty 1 lively 1 keen 1 heavy 1 early 1 deep 1 dark 1 dar 1 cheap 1 MOST 1 -Almost Top 50 lemmatized superlative adverbs; "How do things do to the extreme?" ------------------------------------------------------------------------ 45 most 29 least 6 well 1 hard Top 50 Internet domains; "What Webbed places are alluded to in this corpus?" ---------------------------------------------------------------------------- 1 www.pgdpcanada.net Top 50 URLs; "What is hyperlinked from this corpus?" ---------------------------------------------------- 1 http://www.pgdpcanada.net Top 50 email addresses; "Who are you gonna call?" ------------------------------------------------- Top 50 positive assertions; "What sentences are in the shape of noun-verb-noun?" ------------------------------------------------------------------------------- 6 sammy did n''t 4 deer is not 4 deer is smart 4 hunter is still 4 lightfoot did n''t 4 lightfoot had not 4 lightfoot was just 4 lightfoot was n''t 4 lightfoot was sure 3 _ did _ 3 _ is _ 3 _ was _ 3 deer had just 3 eyes were wide 3 nimble did n''t 3 nimble did not 3 ted said reluctantly 2 _ had _ 2 al did not 2 al had always 2 al was still 2 days grow cold 2 deer is big 2 deer is n''t 2 deer looked anything 2 deer ran n.w. 2 deer ran only 2 deer was unhappy 2 deer was wholly 2 deer were generally 2 eyes are quite 2 eyes watched first 2 eyes were very 2 forest is full 2 forest was no 2 head was slowly 2 hunter did not 2 hunter did nothing 2 hunter got back 2 hunter had not 2 hunter had patience 2 hunter had plenty 2 hunter hunting lightfoot 2 hunter looked surprised 2 hunter saw reddy 2 hunter was sorely 2 hunter was still 2 hunter went on 2 hunter went quite 2 hunter were still Top 50 negative assertions; "What sentences are in the shape of noun-verb-no|not-noun?" --------------------------------------------------------------------------------------- 2 deer is not very 2 forest was no longer 2 hunter got no glimpse 1 area were not as 1 day was not too 1 deer had no idea 1 deer had no trouble 1 deer were not especially 1 eyes had not yet 1 hunters got no glimpse 1 nimble was not upset 1 pack did not suddenly 1 pack was not here 1 snow was not more 1 ted had not only 1 trees were not so 1 wolves has not yet A rudimentary bibliography -------------------------- id = 21619 author = Bailey, Arthur Scott title = The Tale of Nimble Deer Sleepy-Time Tales date = keywords = Jimmy; Mr.; Nimble; Rabbit summary = When Nimble''s mother first looked at him she couldn''t believe she would "Good morning, Mr. Grouse!" said Nimble''s mother. Nimble''s mother hadn''t liked Mr. Grouse''s remark about Foxes. "Quite!" said Nimble''s mother, as she closed her eyes and heaved a deep "There''s nothing," said Nimble to his mother one night, "nothing so good One morning Nimble''s mother said to him, "To-night, just as the moon the rim of the world, for Nimble Deer''s mother wouldn''t wait for anybody Weeks went by; and still Nimble''s mother said no more about visiting [Illustration: Nimble Deer Followed Jimmy Rabbit. "Old dog Spot!" Jimmy Rabbit gasped as he whisked past Nimble. Jimmy Rabbit said that Nimble was _too Nimble asked Jimmy Rabbit a question: "Are you feeling well?" So the next time Nimble found Jimmy Rabbit he asked him that very Jimmy Rabbit didn''t even wait to hear what Nimble said, but whisked away id = 19079 author = Burgess, Thornton W. (Thornton Waldo) title = The Adventures of Lightfoot the Deer date = keywords = Forest; Green; Lightfoot; Paddy; Sammy summary = Sammy watched the hunter enter the Green Forest, then he silently Could you have seen the hunter with the terrible gun and Lightfoot the Now the hunter with the terrible gun who was looking for Lightfoot knew It was a dreadful game the hunter with the terrible gun and Lightfoot When the hunter found the hiding-place Lightfoot had left at the warning These things told the hunter which way Lightfoot had gone. Lightfoot the Deer traveled on through the Green Forest, straight ahead When Lightfoot bounded away through the Green Forest, after watching the Now Lightfoot had known of hunters hiding near water, hoping to shoot The instant Lightfoot saw Paddy the Beaver he knew that for the time Lightfoot, the Green Forest is full of hunters looking for you. Sammy knew all of Lightfoot''s hiding-places. it was Sammy who warned Lightfoot of the coming of the hunter on the id = 4670 author = Burgess, Thornton W. (Thornton Waldo) title = Lightfoot the Deer date = keywords = Forest; Green; Lightfoot; Paddy; Sammy summary = Sammy watched the hunter enter the Green Forest, then he silently as the game Lightfoot the Deer was playing with the hunter hunter might have come within shooting distance before Lightfoot Could you have seen the hunter with the terrible gun and Lightfoot have thought that Lightfoot was hunting the hunter instead of the When the hunter found the hiding-place Lightfoot had left at the warning of Sammy Jay he followed Lightfoot''s tracks for a short These things told the hunter which way Lightfoot had gone. Green Forest, where Lightfoot the Deer lay resting behind a pile Lightfoot kept perfectly still and watched the hunter disappear Now Lightfoot had known of hunters hiding near water, hoping to The instant Lightfoot saw Paddy the Beaver he knew that for the By the way, Lightfoot, the Green Forest is full of hunters looking Sammy knew all of Lightfoot''s hiding-places. id = 41671 author = Kjelgaard, Jim title = Double Challenge date = keywords = Blade; Crestwood; John; Loring; Lorton; Mahela; Pythias; Smoky; Tammie; Ted; Thornton; Valley; Wilson summary = Tammie wouldn''t have gone, Ted strolled up and looked in at the open "Sure," Ted grinned, "I''ll be famous as a deer hunter before I ever am Ted turned up the drive and was halfway to the house when Tammie came Early the next morning, Al let Ted and Tammie off at the camp and turned On the Lorton Road, Ted heard the cars that Tammie had An hour after leaving his house, Ted came to the mouth of Coon Valley. Ted looked down at the place where Smoky Delbert had fallen, and there the center of the thicket, Tammie halted to look down and Ted came up Ted said, "Come on, Tammie." Ted assured the other deer hunters that his camp was reserved for the Tammie, hearing Ted''s voice and thinking he was called, came over to sit That night, back at the Harkness house, Ted took Tammie''s harness from id = 37595 author = Ream, Robert R. title = Ecological Studies of the Timber Wolf in Northeastern Minnesota date = keywords = February; Figure; January; March; Mech; Minnesota; illustration; wolf summary = of Deer Killed by Wolves in Northeastern Minnesota Usually deer are run down from behind, the wolf or wolves biting at _Table 7.--Kill rate of deer by radiotagged wolves and their associates_ two packs of three wolves (one deer per 12 days per wolf). AN ANALYSIS OF THE AGE, SEX, AND CONDITION OF DEER KILLED BY WOLVES IN [Illustration: _Figure 4.--As many wolf-killed deer as possible were _Table 3.--Sex ratios of wolf-killed deer from wilderness areas Wolf-killed deer in our sample, with an average age of 4.7 years, were wolf-killed deer might differ from that of the actual population, we _Table 4.--Age and sex distribution of deer killed by wolves Condition of Wolf-Killed Deer In conclusion, our data on both age and condition of wolf-killed deer The above observations of snow conditions, deer movements, and wolf the winter most of the deer killed by wolves in our study area were not id = 32319 author = Seton, Ernest Thompson title = The Trail of the Sandhill Stag date = keywords = Stag; Yan; illustration; track summary = into the hills every day till I bring out a deer." Yan was a tall, raw trip in the southern hills he came at last on the trail of a deer--dim passed in the snow-clad hills, sometimes on a deer-trail but more So when the first tracking snow came, Yan set out with some comrades After a few miles he came on a great deer-track, so large and sharp And as he neared the great Spruce Hill, Yan yelled a long hurrah! Straight to the very place went Yan, and found the tracks--one like follow the trail over the hills, for deer watch their back track, and out alone, Yan had followed a deer-track into a thicket by what is there was only one track for Yan. At last the chase led away to the great dip of Pine Creek--a mile-wide trail, then seeing Yan crossing the flat, his track went swiftly id = 32891 author = Yerxa, Leroy title = Phantom of the Forest date = keywords = Boody; Robinson; Starr summary = "Almost," Earl Robinson said, and twisted the wheel again. Robinson and Roy Starr got out. "Nobody I know," Roy said, and turned away so he wouldn''t have to stare "Hit sometime before the snow came," Robinson said. Robinson turned away, looking toward the car. Earl Robinson said solemnly: cups on the kitchen table, Robinson cornered Norm Boody and led him into "You better let Marge sleep," Mrs. Boody said. "I wouldn''t worry, Mrs. Boody," Robinson said. "It _was_ rugged last night, all right," Roy Starr said. Earl Robinson said: "Look," Larson said abruptly, "you don''t believe that phantom buck "_I_ can''t sleep," Glenn Starr said. "Okay, Bill," Robinson said. "About the phantom buck," Robinson said. The Doctor said good night to Mrs. Boody and came out Norm Boody came out of the house with Roy Starr''s rifle. "You may as well face it," Robinson said.