Means (Cause_change_of_scalar_position)
Stats
- Average : 0.487448
- Std dev. : 0.0317773
- Min : 0.455671
- Max : 0.617512
- FEs : 13
Descriptors
Too few elements
Legend = verbs; nouns; adjectives; proper noun; french
- term 0.617512
- transition 0.593457
- component 0.569342
- adapt 0.565945
- graft 0.559812
- switch 0.550829
- weave 0.534763
- use 0.532969
- envisage 0.532675
- production 0.532452
- signal 0.532001
- combination 0.531953
- experiment 0.531845
- simulate 0.529385
- flexible 0.527579
- adjust 0.527452
- loose 0.523237
- switch 0.520603
- curler 0.517799
- evolve 0.516774
- barter 0.512787
- change 0.511532
- introduce 0.505522
- mounting 0.503323
- strip 0.499182
- dismantle 0.496123
- structure 0.494952
- tie 0.494554
- differentiate 0.493728
- uniform 0.493329
- modified 0.493069
- force 0.490961
- mop 0.487939
- shift 0.487883
- realign 0.487079
- quirk 0.486765
- accelerate 0.485978
- rubber 0.483151
- belt 0.481845
- model 0.481726
- superimpose 0.481371
- stave 0.481109
- adaptation 0.480325
- trigger 0.478940
- shunt 0.478388
- different 0.477313
- model 0.476848
- speed 0.476778
- complicated 0.476692
- operate 0.476603
- photon 0.476524
- laminate 0.475635
- pinafore 0.474816
- combine 0.474632
- collar 0.474500
- repulsive 0.473455
- fit 0.473099
- typify 0.472129
- plug 0.471990
- hybrid 0.471877
- transformation 0.470910
- distinguish 0.470212
- shoe 0.469113
- cut 0.469101
- streamlined 0.468565
- sandalwood 0.468503
- lag 0.468341
- measure 0.467179
- derivative 0.467151
- suit 0.466822
- tinker 0.466750
- regime 0.465829
- procurement 0.465475
- imprinting 0.465413
- makeup 0.465313
- scrunch 0.465203
- synchronize 0.464939
- jet 0.464462
- mimic 0.462694
- l'or 0.462635
- weave 0.461965fwversa 0.461882
- modify 0.461443
- fur 0.460590
- bureaucratic 0.459739
- smooth 0.458947
- linkage 0.458941
- chain 0.458768
- dynamic 0.458337
- imitate 0.458158
- inefficient 0.457884
- styling 0.457684
- owd 0.457317
- outdate 0.457242
- ease 0.456844
- chaotic 0.456743
- garment 0.456715
- gear 0.456630
- characterize 0.455879
- tremolo 0.455671
by infilling.
by putting yourself on the saddle of an imaginary bicycle and travelling back in time to the turn-of-the-century.
by changing agencies.
by incorporating lexical stress into the representation.
by mimicking the interactions that normally occur between the mucoid component of the tear film and the corneal surface.
by going public.
by cutting the number of firms used.
by vertical integration.
by using shock tactics similar to those of President Menem of Argentina.
by wearing a pullover , slip-off shoes and no underwear.
through new legislation.
by improving your on-course tactics.
by expanding capital intensive industries which leave the poorest sectors of that society completely untouched.
NNinfill
VVput
NNsaddle
JJimaginary
NNbicycle
VVtravel
NNtime
NNturn-of-the-century
VVchange
NNagency
VVincorporate
JJlexical
NNstress
NNrepresentation
VVmimic
NNinteraction
VVoccur
JJmucoid
NNcomponent
VVtear
NNfilm
JJcorneal
NNsurface
VVgo
NNpublic
VVcut
NNnumber
NNfirm
VVuse
JJvertical
NNintegration
VVuse
NNshock
NNtactic
JJsimilar
NPPresident
NPMenem
NPArgentina
VVwear
NNpullover
NNshoe
NNunderwear
JJnew
NNlegislation
VVimprove
NNon-course
NNtactic
VVexpand
JJcapital
JJintensive
NNindustry
VVleave
JJpoor
NNsector
NNsociety
JJuntouched
Cluster #1 : 3 instances
Cluster #17 : 3 instances
Cluster #35 : 4 instances
wear
pullover
shoe
underwear
Cluster #1   3 instances
- cut 0.876772
- put 0.876211
- tear 0.854816
- rip 0.834460
- tip 0.823773
- scrape 0.821031
- tie 0.812151
- roll 0.807266
- strip 0.789630
- throw 0.785094
- pull 0.780935
- drag 0.779921
- pin 0.771755
- wipe 0.761627
- drop 0.753710
- shove 0.753506
- dust 0.750812
- lay 0.747709
- stick 0.739142
- sling 0.738016
- break 0.737822
- lop 0.737395
- push 0.737239
- slip 0.730108
- kick 0.725596
- turn 0.722988
- toss 0.713395
- hand 0.712432
- bounce 0.709905
- blow 0.706215
- ricochet 0.704108
- hack 0.700246
- dangle 0.693850
- bob 0.693587
- shuffle 0.688225
- hang 0.687581
- stave 0.686204
- bogged 0.686028
- crack 0.685635
- shoot 0.681839
- nip 0.678924
- brute 0.677952
- slide 0.677375
- whittle 0.670314
- whiz 0.669928
- flop 0.669132
- ward 0.667875
- smooth 0.661753
- clamp 0.659153
- bring 0.658673
- flap 0.658065
- rub 0.657321
- bash 0.656855
- saw 0.656652
- shave 0.656418
- cannon 0.656242
- snatch 0.653457
- lift 0.653148
- whack 0.653023
- set 0.651820
- backside 0.649944
- snip 0.648524
- cascade 0.648445
- flick 0.647301
- tumble 0.647227
- sweep 0.647086
- plunge 0.646894
- slither 0.646663
- prise 0.642610
- fob 0.642260
- stamp 0.641723
- plume 0.641447
- reel 0.638615
- wriggle 0.637931
- balance 0.637905
- banisters 0.636370
- sock 0.635291
- pare 0.634441
- keep 0.634300
- brush 0.633578
- slap 0.631282
- winch 0.629818
- pluck 0.628360
- haul 0.628132
- peel 0.625110
- braid 0.624856
- gun 0.624119
- head 0.623205
- singe 0.622867
- fend 0.622516
- swipe 0.619877
- rounded 0.616669
- thrust 0.616191
- thumb 0.615273
- inch 0.614454
- plonk 0.614061
- career 0.613802
- burn 0.613793
- foot 0.613765
- pile 0.613276
Cluster #17   3 instances
- industry 0.907603
- sector 0.882470
- expand 0.830697
- commerce 0.817809
- manufacturing 0.802863
- tourism 0.744963
- nationalize 0.738068
- expansion 0.737345
- industrial 0.721560
- deregulation 0.715898
- telecoms 0.713148
- enterprise 0.712663
- retailing 0.707798
- commercial 0.692603
- multinational 0.685247
- aerospace 0.681123
- retail 0.679710
- competitiveness 0.676525
- telecommunication 0.668456
- boom 0.666352
- manufacture 0.666230
- infrastructure 0.663358
- booming 0.657507
- textile 0.657231
- deregulate 0.655448
- economy 0.654445
- agriculture 0.652024
- telecommunications 0.648001
- growth 0.641119
- textile 0.640086
- export 0.639997
- footloose 0.639494
- recession 0.637928
- purchasing 0.637494
- privatising 0.636940
- nationalization 0.636067
- diversified 0.631201
- innovate 0.622830
- shipbuilding 0.622242
- manufacture 0.617998
- transatlantic 0.611522
- consultancy 0.611219
- diversify 0.610917
- privatised 0.607274
- headhunting 0.605653
- market 0.605528
- competitive 0.604716
- outlet 0.603561
- electronics 0.601577
- pharmaceutical 0.601462
- profitable 0.596893
- downturn 0.596160
- retail 0.595534
- workforce 0.592612
- broadcasting 0.592610
- trade 0.587775
- unprofitable 0.586211
- automotive 0.582282
- producer 0.580295
- tncs 0.579603
- overseas 0.578967
- automobile 0.576652
- cutback 0.574731
- marketing 0.574436
- tncs 0.573382
- agricultural 0.573006
- multinational 0.571803
- prosperity 0.570252
- banking 0.569744
- decline 0.568868
- innovation 0.568181
- supplier 0.568172
- service 0.565061
- export 0.564706
- investment 0.563397
- finance 0.563121
- transport 0.562884
- airline 0.562267
- internationalization 0.560114
Cluster #35   4 instances
- jean 0.965434
- hat 0.926006
- wear 0.925812
- dress 0.924618
- pullover 0.907550
- trouser 0.907538
- short 0.897483
- sweater 0.895608
- coat 0.894116
- shoe 0.890828
- shirt 0.890720
- underwear 0.880294
- gown 0.870210
- pant 0.868704
- waistcoat 0.864394
- blouse 0.864278
- jacket 0.855233
- tweed 0.850357
- wig 0.849732
- leggings 0.848100
- skirt 0.847319
- bikini 0.845207
- sock 0.844810
- shawl 0.843696
- belt 0.842950
- boater 0.841216
- blonde 0.838265
- clothe 0.838207
- sandalwood 0.833558
- denim 0.826672
- tan 0.824750
- uniform 0.824650
- smock 0.823479
- suit 0.822280
- tights 0.822169
- flannel 0.821688
- maroon 0.820328
- starch 0.819707
- trilby 0.819697
- brogue 0.818793
- scarf 0.817892
- turban 0.815732
- suede 0.815616
- baggy 0.815452
- beret 0.808231
- quilt 0.805293
- tartan 0.804613
- scarves 0.803051
- striped 0.802982
- petticoat 0.800851
- lace 0.800803
- corduroy 0.797680
- dress 0.797084
- lipstick 0.796474
- crepe 0.794344
- cardigan 0.794195
- beige 0.793902
- smart 0.792257
- sweatshirt 0.791378
- moustache 0.790542
- leotard 0.790132
- balaclava 0.787800
- jumper 0.785990
- dungaree 0.783571
- stocking 0.783300
- headband 0.782784
- tracksuit 0.781661
- duffel 0.781616
- costume 0.777082
- haired 0.776591
- sleeveless 0.776162
- garment 0.775578
- breech 0.773893
- crochet 0.773698
- permed 0.771599
- collar 0.770744
- hair 0.769594
- silk 0.767036
- apron 0.765893
- blazer 0.764345
- straw 0.763166
- jerkin 0.761313
- fawn 0.759658
- curly 0.759645
- jersey 0.758952
- flowered 0.758299
- overcoat 0.757004
- nightdress 0.756271
- calico 0.755600
- sunglasses 0.755362
- brunette 0.754782
- fur 0.754542
- eyeshadow 0.753196
- hood 0.753136
- panties 0.751637
- dashing 0.751117
- chunky 0.748735
- outfit 0.747248
- maple 0.746518
- headdress 0.744195