Corsican-Myths

Because one wishes to show an exemplary table of the sacrifice of some, and sometimes the burning partisans of the French bosom join on this point the freedom fighters, the figure concerning the Corsicans is inordinately inflated. Like, in Algeria where the martyrs became deaths of which the number increases as the distance of the memory, Corsican deaths of the First World War are exposed to the admiration of all. Thus the casualties become deaths and that deaths of the Spanish influenza fell to the field from honor. In consideration of which, go on the island, one will not hesitate in front of the war memorials furnished well (but of others on the Continent are it as much) to evoke you the 40000, even the 50000 died, and if you have a little curiosity, you will be astonished that the near total of the mobilizable male population disappeared (it indeed a little more than 52,000 had mobilized there and engaged) whereas your interlocutor could be born and be there for you to say it. You believe that I invent, but not, go this time on the Internet, this marvellous buoy of insularity, sail on the sites (necessarily nationalist) and you will see that the most various figurings and most delirious exchange themselves there like as many narcotics destroying any critical judgment, and any desire to stop looking at the navel.

The data, however, exist while seeking well (oh! yes!). Let us start with those provided by the censuses. If the revisions operated by Louis Henry in 1948 do not announce anything in particular for the censuses of 1901 and 1911 (allowed opinion by Damiani, but the appendix on demography already showed that dissenting evaluations exist), everyone agrees to consider that of 1921 starts to diverge from with reality, in particular because of double countings. Let us look at however one moment this table: Corsica loses 2,4% of his population between the two censuses which frame the first world war, while passing from 288820 inhabitants with 281959 is a lack of 6861 inhabitants. If the various rectifying evaluations are retained, the following results are obtained:

Kolodny (real population) 270000 / 255000 (- 5,6 %)
Kolodny (evaluation) 260000/250000 (- 3,8 %)
Renucci 245000/230000 (- 6 %)

That is to say a relatively modest row (of the 73è row for the evaluation of least low deficit to the 46è row for the most marked deficit). In the table of the census, where only, apart from Corsica, the departments of Charente, of the Low Alps and the Pyrenees Orientales have subjects to deposit results, one immediately locates the departments strongly touched by the conflict, those which, close to the front, saw their population fleeing towards the interior, in particular towards the Seine and the Seine and Oise, which explains their rate of loss of considerable population, losses due essentially to the migrations. After war, Corsica will know a movement of emigration which continues that of pre-war period, but the immediate post-war period (1919-1920) does not know as positive migratory movement only the return of the soldiers however two thirds choose not to return (754 on a sample of 1129 taken in six different classes of incorporation - to see Olivier Maestrati, COp cit.). Also the expatriation is a phenomenon which continues (+ 8399 expatriates). On the other hand, it is advisable to add the natural balance and to take into account the evolutions of migratory balance (foreigners and nationals). The whole brings back to us to an “unexplained” deficit of 7400 inhabitants on the basis of real population.

Table of 1911 and 1921 censuses

Official Population

	1911	1921	Evolution	Rank			1911	1921		Evolution	Rank
Meuse	277955	207309	-25,4%		1	Vaucluse	238656		219602	-8,0%	46
Aisne	530226	421515	-20,5%		2	Côtes du Nord	605523		557824	-7,9%	47
Marne	436310	366734	-15,9%		3	Vienne	332276		306248	-7,8%	48
Alpes (Hautes)	105083	89275	-15,0%		4	Ain	342482		315757	-7,8%	49
Alpes (Basses)	107231	91882	-14,3%		5	Eure & Loir	272255		251255	-7,7%	50
Creuse	266188	228344	-14,2%		6	Savoie (Haute)	255137		235668	-7,6%	51
Lot	205769	176889	-14,0%		7	Marne (Haute)	214765		198865	-7,4%	52
Ariège	198725	172851	-13,0%		8	Loiret	364061		337224	-7,4%	53
Somme	520161	452624	-13,0%		9	Pas de Calais	1068155		989967	-7,3%	54
Ardennes	318896	277811	-12,9%		10	Loir & Cher	271231		251528	-7,3%	55
Tarn & Garonne	182537	159559	-12,6%		11	Charente Inférieure	450871		418310	-7,2%	56
Gers	221994	194406	-12,4%		12	Sarthe	419370		389235	-7,2%	57
Mayenne	297732	262447	-11,9%		13	Pyrénées (Basses)	433318		402981	-7,0%	58
Vosges	433914	383684	-11,6%		14	Belfort (territoire)	101386		94338	-7,0%	59
Corrèze	309646	273808	-11,6%		15	Puy de Dôme	525916		490560	-6,7%	60
Loire (Haute)	303838	268910	-11,5%		16	Maine & Loire	508149		474786	-6,6%	61
Saône (Haute)	257606	228348	-11,4%		17	Eure	323651		303159	-6,3%	62
Lozère	122738	108822	-11,3%		18	Finistère	809771		762514	-5,8%	63
Ardèche	331801	294308	-11,3%		19	Oise	411028		387760	-5,7%	64
Meurthe & Mos.	564730	503810	-10,8%		20	Morbihan	578400		546047	-5,6%	65
Cantal	223361	199402	-10,7%		21	Isère	555911		525522	-5,5%	66
Manche	476119	425512	-10,6%		22	Aube	240755		227839	-5,4%	67
Orne	307433	274814	-10,6%		23	Doubs	299935		285022	-5,0%	68
Lot & Garonne	268083	239972	-10,5%		24	Aude	300537		287052	-4,5%	69
Yonne	303889	273118	-10,1%		25	Gard	413458		396169	-4,2%	70
Aveyron	369448	332940	-9,9%		26	Indre & Loire	341205		327743	-3,9%	71
Pyrénées (Htes)	206105	185760	-9,9%		27	Seine & Marne	363561		349234	-3,9%	72
Cher	337810	304800	-9,8%		28	Loire Inférieure	669920		649723	-3,0%	73
Nièvre	299312	270148	-9,7%		29	Calvados	396318		384730	-2,9%	74
Indre	287673	260535	-9,4%		30	*Corse*	*288820*		*281959*	*-2,4%*	75
Drôme	290894	263509	-9,4%		31	Var	330755		322945	-2,4%	76
Vendée	438520	397292	-9,4%		32	Garonne (Haute)	432126		424582	-1,7%	77
Jura	252713	229062	-9,4%		33	Gironde	829095		819404	-1,2%	78
Dordogne	437432	396742	-9,3%		34	Loire	640549		637130	-0,5%	79
Savoie	247890	224874	-9,3%		35	Seine Inférieure	877383		880671	0,4%	80
Vienne (Haute)	384736	350235	-9,0%		36	Alpes maritimes	356338		357759	0,4%	81
Nord	1961780	1787918	-8,9%		37	Hérault	480484		488215	1,6%	82
Tarn	324090	295588	-8,8%		38	Pyrénées Orientales	212986		217503	2,1%	83
Charente	346424	316279	-8,7%		39	Rhône	915581		956566	4,5%	84
Allier	406291	370950	-8,7%		40	Bouches du Rhône	805532		841996	4,5%	85
Landes	288902	263937	-8,6%		41	Seine	4154042		4411691	6,2%	86
Côte-d'Or	350044	321088	-8,3%		42	Seine & Oise	817617		921673	12,7%	87
Saône &Loire	604446	554816	-8,2%		43
Sèvres (Deux-)	337627	310060	-8,2%		44	France *	*39601509*		*37500017*	*-5,3%*	67
Ille & Vilaine	608098	558574	-8,1%		45	* without Alsace-Lorraine

Real Population

1911Prés.	1911.	1921	Evolution	Rank		1911.	1921.	Evolution	Rank
Meuse	274 706	205 043	-25,4%	1	Ille et Vilaine	603287	553646	-8,2%	45
Aisne	526 788	418 348	-20,6%	2	Sèvres (Deux-)	335115	308243	-8,0%	46
Marne	431 832	363 847	-15,7%	3	Vienne	330507	304337	-7,9%	47
Alpes (hautes)	102 203	86 488	-15,4%	4	Côtes du Nord	592840	546350	-7,8%	48
Alpes (basses)	103 969	89 419	-14,0%	5	Eure et Loir	268935	247863	-7,8%	49
Lot	202 402	174 662	-13,7%	6	Saône et Loire	599279	552524	-7,8%	50
Ardennes	316 825	275 613	-13,0%	7	Vaucluse	237184	219082	-7,6%	51
Ariège	192 478	167 692	-12,9%	8	Savoie (Haute)	251865	232695	-7,6%	52
Somme	514 929	449 596	-12,7%	9	Loiret	360823	333569	-7,6%	53
Creuse	250 600	218 825	-12,7%	10	Loir et Cher	269486	249173	-7,5%	54
Gers	221 158	193 226	-12,6%	11	Marne (Haute)	212962	196911	-7,5%	55
Tarn etGaronne	181 186	158 769	-12,4%	12	Sarthe	416383	385923	-7,3%	56
Mayenne	295 908	260 778	-11,9%	13	Maine et Loire	506905	471727	-6,9%	57
Vosges	432 035	380 972	-11,8%	14	Charente Infér.	445166	414297	-6,9%	58
Ardèche	327 580	289 323	-11,7%	15	Pas de Calais	1059824	988110	-6,8%	59
Loire ( Haute)	298 942	264 188	-11,6%	16	Pyrénées (Basses	430437	401778	-6,7%	60
Saône ( Haute)	255 883	226 392	-11,5%	17	Morbihan	570465	534044	-6,4%	61
Lozère	117 301	104 341	-11,0%	18	Puy de Dôme	512747	480013	-6,4%	62
Manche	474 132	422 853	-10,8%	19	Finistère	795308	746196	-6,2%	63
Meurthe & Mos.	561 060	501 276	-10,7%	20	Oise	407681	382724	-6,1%	64
Orne	304 152	272 689	-10,3%	21	Eure	318809	299651	-6,0%	65
Cher	335 139	300 865	-10,2%	22	*Corse*	*270218*	*254958*	*-5,6%*	66
Aveyron	365 239	328 337	-10,1%	23	Isère	550164	520286	-5,4%	67
Corrèze	291 546	262 315	-10,0%	24	Aube	238690	226884	-4,9%	68
Lot etGaronne	265 192	238 725	-10,0%	25	Doubs	295638	281439	-4,8%	69
Yonne	300 542	271 429	-9,7%	26	Aude	298164	285687	-4,2%	70
Nièvre	296 691	268 034	-9,7%	27	Calvados	393568	377320	-4,1%	71
Drôme	288 134	260 430	-9,6%	28	Alpes maritimes	400672	384625	-4,0%	72
Indre	285 350	258 048	-9,6%	29	Indre et Loire	339051	325870	-3,9%	73
Dordogne	434 186	392 941	-9,5%	30	Gard	407989	393469	-3,6%	74
Cantal	208 884	189 103	-9,5%	31	Seine et Marne	357966	346360	-3,2%	75
Jura	249 999	226 395	-9,4%	32	Var	332879	322853	-3,0%	76
Vendée	436 814	395 991	-9,3%	33	Loire Inférieure	666385	646667	-3,0%	77
Pyrénées (Htes)	202 267	183 489	-9,3%	34	Garonne (Haute)	423635	418253	-1,3%	78
Allier	405 288	368 341	-9,1%	35	Gironde	826208	818392	-0,9%	79
Nord	1 953 413	1 778 174	-9,0%	36	Loire	637425	632891	-0,7%	80
Charente	343 870	313 164	-8,9%	37	Seine Inférieure	865571	871043	0,6%	81
Vienne (Haute)	378 629	345 435	-8,8%	38	Hérault	478180	487833	2,0%	82
Savoie	242 090	220 933	-8,7%	39	Pyrénées Orient.	211737	216827	2,4%	83
Belfort (terr. de)	101 287	92 584	-8,6%	40	Rhône	903864	943359	4,4%	84
Côte-d'Or	345 958	316 306	-8,6%	41	Bouch. du Rhône	808166	853439	5,6%	85
Landes	288 431	264 013	-8,5%	42	Seine	4090028	4325609	5,8%	86
Tarn	319 179	292 169	-8,5%	43	Seine et Oise	806103	916783	13,7%	87
Ain	339 627	311 153	-8,4%	44	*France*	*39192133*	*37102417*	*-5,3%*

Attempt of a losses evaluation

Application of a calculation of theoretical evaluation of population equalizes with :

Real Population 1911 - expat differential (1921-1911) + immigration differential from other departements (1921-1911, negative result) + foreign immigration differential (1921-1911) + annual natural balances (from 1911 to 1921).

Download the evaluation file

For a reasonable estimate of the expatriation of the nationals of a department, we retained the use of the abundant data by the censuses on the official population and the real population present the day of the census. The data for a census is not relevant in oneself but the difference of the two variations out of two successive censuses enables us to put in glance a population nonpresent in 1921 with a nonpresent population in 1911. That determines the evolution of the nonpresent population and to constitute little, under some reserves related to the characteristics of such or such department, an acceptable estimate of the movement of expatriation between these two censuses.

The comparison between the theoretical population and the population listed in 1921 gives the figure of 7108 souls for what it is necessary to add approximately 250 deaths of repatriated soldiers. For this last data, it is advisable to be careful because if it is relevant in the case of departments far away from the zone of conflict, on the other hand, it is an aberrant data in the departments close to the front, the departments with strong population and thus with hospital infrastructures developed as in the case of some departments in which installations were built precisely to accommodate the casualties in excess, as the intensification of the conflict. In these departments, the data of the military deaths following wound increases the departmental losses whereas they are not mobilized departments in question. This is why the interdepartmental comparison should not take them into account.

In addition, the reading of the following table shows negative missing populations, i.e. real populations more important than than the recorded migratory movements or the natural balance let wait. Several reasons with that :

the departments of the war front present important statistical gaps
some did not know repatriation of the refugees immediately post-war period
the great urban areas keep beside their limits these populations
the evaluation of the expatriation by difference in legal evolution of the populations and presents is very underestimated in these departments (great proximity of the areas of North and the East with the Paris region, area of natural fold, which allows listed to be present the day of the census while residing elsewhere).

It is not thus astonishing to find at the beginning of list the ten departments of the front (except the remarkable case of Lozere which is intercalated), and at the end of the list all the departments with very strong urban areas which accommodates wounded and taken refuge (Bouches du Rhone, the Rhone, Paris region, the Gironde, etc the case of the Alpes Maritimes comes out from another problems it is one of the rare cases of real population higher than the official (legal) population, situation in relation to the long tradition of holiday of the French Riviera.

Comparison with the other departements

1921	theorical Pop	lacking Pop.	Evol.	Rk	1921	theorical Pop	Real Pop	lacking Pop.	Evol.	Rk
Aisne	541 988	123 640	23,5%	1	Ille etVilaine	585 642	553 646	31 996	5,3%	44
Meuse	260 307	55 264	20,1%	2	Savoie	233 596	220 933	12 663	5,2%	45
Marne	434 355	70 508	16,3%	3	Tarn	308 691	292 169	16 522	5,2%	46
Ardennes	325 786	50 173	15,8%	4	Lot	185 056	174 662	10 394	5,1%	47
Somme	524 815	75 219	14,6%	5	Loir et Cher	262 382	249 173	13 209	4,9%	48
Pas de Calais	1 121 257	133 147	12,6%	6	Pyrénées Orientales	227 114	216 827	10 287	4,9%	49
Vosges	434 586	53 614	12,4%	7	Loiret	351 066	333 569	17 497	4,8%	50
Nord	2 004 546	226 372	11,6%	8	Eure et Loir	260 868	247 863	13 005	4,8%	51
Lozère	117 901	13 560	11,6%	9	Allier	387 551	368 341	19 210	4,7%	52
Meurthe etMosle	562 581	61 305	10,9%	10	Charente	329 396	313 164	16 232	4,7%	53
Oise	424 685	41 961	10,3%	11	Seine et Marne	362 695	346 360	16 335	4,6%	54
Corrèze	292 305	29 990	10,3%	12	Pyrénées ( Hautes)	191 950	183 489	8 461	4,2%	55
Creuse	243 981	25 156	10,0%	13	Charente Inférieure	432 527	414 297	18 230	4,1%	56
Vendée	437 761	41 770	9,6%	14	Eure	312 699	299 651	13 048	4,1%	57
Finistère	821 944	75 748	9,5%	15	Loire Inférieure	671 760	646 667	25 093	3,8%	58
Cantal	207 614	18 511	8,9%	16	Ain	323 840	311 153	12 687	3,7%	59
Loire ( Haute)	290 536	26 348	8,8%	17	Seine Inférieure	902 989	871 043	31 946	3,7%	60
Alpes (hautes)	94 969	8 481	8,3%	18	Tarn etGaronne	165 391	158 769	6 622	3,7%	61
Alpes (basses)	98 014	8 595	8,3%	19	Aube	235 441	226 884	8 557	3,6%	62
Saône ( Haute)	247 447	21 055	8,2%	20	Drôme	270 227	260 430	9 797	3,4%	63
Landes	287 463	23 450	8,1%	21	Orne	282 987	272 689	10 298	3,4%	64
Belfort (terri d)	100 735	8 151	8,0%	22	Côte-d' Or	327 934	316 306	11 628	3,4%	65
Côtes du Nord	593 738	47 388	8,0%	23	Isère	537 981	520 286	17 695	3,2%	66
Ariège	182 766	15 074	7,8%	24	Sarthe	398 930	385 923	13 007	3,1%	67
Ardèche	314 961	25 638	7,8%	25	Puy de Dôme	495 302	480 013	15 289	3,0%	68
Yonne	294 862	23 433	7,8%	26	Aude	294 356	285 687	8 669	2,9%	69
Aveyron	356 169	27 832	7,6%	27	*Corse*	*262 066*	*254 958*	*7 108*	*2,6%*	70
Saône etLoire	597 354	44 830	7,5%	28	Gers	198 848	193 226	5 622	2,5%	71
Morbihan	576 398	42 354	7,4%	29	Maine et Loire	484 299	471 727	12 572	2,5%	72
Mayenne	282 741	21 963	7,4%	30	Lot etGaronne	244 735	238 725	6 010	2,3%	73
Vienne (Haute)	373 437	28 002	7,4%	31	Indre et Loire	332 226	325 870	6 356	1,9%	74
Pyrénées (Basses	433 384	31 606	7,3%	32	Vaucluse	222 983	219 082	3 901	1,6%	75
Indre	278 368	20 320	7,1%	33	Loire	642 883	632 891	9 992	1,6%	76
Sèvres ( Deux-)	330 736	22 493	6,7%	34	Gard	399 616	393 469	6 147	1,5%	77
Dordogne	421 501	28 560	6,6%	35	Calvados	380 961	377 320	3 641	0,9%	78
Vienne	324 820	20 483	6,2%	36	Bouches du Rhône	860 709	853 439	7 270	0,9%	79
Cher	321 632	20 767	6,2%	37	Gironde	820 248	818 392	1 856	0,2%	80
Manche	451 049	28 196	5,9%	38	Hérault	485 033	487 833	-2 800	-0,6%	81
Doubs	298 529	17 090	5,8%	39	Seine	4 226 874	4 325 609	-98 735	-2,4%	82
Marne (Haute)	208 742	11 831	5,6%	40	Seine et Oise	894 584	916 783	-22 199	-2,8%	83
Jura	240 019	13 624	5,4%	41	Garonne (Haute)	404 706	418 253	-13 547	-3,2%	84
Savoie (Haute)	246 339	13 644	5,4%	42	Rhône	909 152	943 359	-34 207	-3,8%	85
Nièvre	284 078	16 044	5,4%	43	Var	308 122	322 853	-14 731	-4,4%	86
					Alpes maritimes	359 525	384 625	-25 100	-6,3%	87

Death rate in the Army Regions and description of the relationship with the expat rate

reg_mil

Source : L’Impartial Français, March 15th 1924.

Only the losses of the soldiers and non-commissioned officers are indexed and this counting rests on the first censuses carried out and not on the exploitation of the army files. The same identified defects concerning the war memorials are found there. Moreover, other biases seem the comparatively high death rate of the areas of the medical back (Orleans, Le Mans, Limoges, etc) which enter the deaths in the hospitals. In spite of this last bias, this table is invaluable because it will enable us to test our assumption of statistical relation between death rate and net expatriation rate. The regroupings of the departments to evaluate the rate of expatriation per military region is carried out in “whole departments” (in other words the departments shared between military regions were allotted to one or the other according to the localization of the prefecture. An exception however for the military Government of Paris which receives the reinforcement of the Seine & Oise. The result obtained is the following for a net expat rate in 1911 on the basis of interdepartmental exchange of population really noted (matrix 87 X 87). The concept of expatriation is to be distinguished from migratory balance because it evaluates the combination of migratory balances through several generations and thus incorporates past movements. This data thus does not merge with the annual migratory balance compared between two censuses.

	emigration	immigration	residents	Net Expat. rate	Death rate
1 RM	165889	111711	903950	6,0%	14,2%
2 RM	140761	113164	484113	5,7%	13,8%
3 RM	187780	294266	796601	-13,4%	17,0%
4 RM	153646	101035	446219	11,8%	20,0%
5 RM	168429	120198	450993	10,7%	20,2%
6 RM	123500	176754	533600	-10,0%	13,7%
7 RM	136448	87801	422728	11,5%	17,4%
8 RM	208394	103638	555235	18,9%	19,3%
9 RM	169182	131170	648743	5,9%	17,7%
10 RM	155547	68131	549366	15,9%	19,5%
11 RM	182815	92623	800191	11,3%	18,6%
12 RM	209854	86314	586159	21,1%	19,6%
13 RM	206493	111129	692223	13,8%	17,6%
14 RM	142564	85514	493213	11,6%	17,6%
15 RM	202846	228770	861230	-3,0%	11,9%
16 RM	165548	105850	589784	10,1%	16,9%
17 RM	139810	94894	537633	8,4%	17,5%
18 RM	143196	149950	745898	-0,9%	15,5%
20 RM	77828	67135	298616	3,6%	16,9%
GL	51992	134371	297116	-27,7%	12,3%
GP	163171	831275	1316387	-48,30%	10,5%

Evaluation before the creation of the Army regions of Nancy and Epinal (6th RM modified)
Algiers is not present (less significative regarding the mobilisation rules in that area)

A strong dispersion of the death rates coud be noticed but that of indicators of expat movements as well as shown by the graph below. The linear relationship is accurate with a regression coefficient at 76% and the graph analysis shows a strong nearness of the non linear coorelation curve with the regression line. A global census of the losses registred on the War Memorials could allow us to strenghten the relationship. For the moment, be glad to consider this serie produced at the sole military region level, noticying that if we added Corsica with a net expat rate at 32,8 % and a death rate at 22 % on the basis of engaged born in Corsica (11325 killed), this one would contribute to reinforce the relationship much more, this latter being much more "linearized" (red dot on the graph).

correlation

To be complete, let us add that the application of a weighting on the basis of coefficient 1 representative the absence of clear expatriation (what is the case for the national average, the expatriation abroad being excluded from calculation) makes it possible to tighten the variations appreciably. Thus the standard deviation before correction of the series is of 2,5% compared with 1,7% after correction. Finally the graph hereafter watch groups of dots before correction and the line of the corrected points. The application of the correction to the death rate of Corsica would make fall this one at 15% is 7700 losses (not far from the counting carried out on the basis of army file, which counts 8007 losses).

correctif_correlation

Sources

Répertoires des recensements de 1911 et 1921, éd. Imprimerie Nationale, 1912 et 1922
Histoire de la population française, 4è tome, dir. Jacques Dupâquier, PUF, 1988
Atlas ethno-historique de la Corse
INED
Recueil des recensements, Imprimerie Nationale, 1912, 1922
Statistiques du mouvement de la population, Imprimerie nationale 1911-1921 (4 vol)
Statistiques sanitaires de la France, Imprimerie administrative Ministère de l’hygiène, de l’assistance et de la prévoyance sociale, 1911-1920 (10 vol) [Ministry for hygiene, the assistance and the social welfare]