Measuring Social Integration Through Participation: Categorizing Organizations and Leisure Activities in the Displaced Karelians Interview Archive using LLMs
Digitized historical archives make it possible to study everyday social life on a large scale, but the information extracted directly from text often does not directly allow one to answer the research questions posed by historians or sociologists in a quantitative manner. We address this problem in a large collection of Finnish World War II Karelian evacuee family interviews. Prior work extracted more than 350K mentions of leisure time activities and organizational memberships from these interviews, yielding 71K unique activity and organization names -- far too many to analyze directly. We develop a categorization framework that captures key aspects of participation (the kind of activity/organization, how social it typically is, how regularly it happens, and how physically demanding it is). We annotate a gold-standard set to allow for a reliable evaluation, and then test whether large language models can apply the same schema at scale. Using a simple voting approach across multiple model runs, we find that an open-weight LLM can closely match expert judgments. Finally, we apply the method to label the 350K entities, producing a structured resource for downstream studies of social integration and related outcomes.
Figures & tables
Figure 1: A single interview example with entities pertaining to the husband (yellow) and wife (blue) highlighted. Translated from Finnish, preserving typographic features of the original data. Note: Names and dates have been changed.
Top 10 Hobbies
handicrafts ( käsityöt ) — 31,780
fishing ( kalastus ) — 20,222
literature ( kirjallisuus ) — 13,128
gardening ( puutarhanhoito ) — 10,519
reading ( lukeminen ) — 9,324
hunting ( metsästys ) — 6,287
Table 1: Top 10 most frequently mentioned hobbies and organizations. Finnish terms in italics.
Figure 2: Distribution of hobby and organization mentions across entity ranks. Hobbies (red) show concentrated distribution in the first few mentions, with some 7.6k unique entities, while organizations (blue) show a long tail extending beyond 60k unique entities.
Q1 – Categories
Q2 – Group Size
Professional/Work
Alone
Cultural/Traditional
Small group
Religious/Spiritual
Large group
Sports/Physical activity
Non-definable
Creative/Artistic
Data error
Educational/Academic
Q3 – Regularity
Table 2: Questionnaire schema showing all options for each question in our final round of annotations.
Model
Avg F1
Qwen2.5-72B-Instruct
65.0
Qwen3-235B-A22B
68.2
DeepSeek-R1-Distill-Llama-70B
62.5
Meta-Llama-3.3-70B-Instruct
73.0
Llama-4-Scout-17B-16E
70.4
Mistral-Large-Instruct-2407
74.6
Table 3: Average F-scores of each model on the evaluation set (n=50).
Method
Schema
Q1
Q2
Q3
Q4
Avg
Orig. prompt
Full
77.0
85.4
73.6
54.6
72.7
Best prompt
Full
78.2
85.8
71.7
55.9
72.9
7 prompt ens.
Coarse
80.0
87.7
76.8
62.7
76.8
7× orig. ens.
Coarse
76.9
87.4
79.9
60.0
76.1
7 prompt ens.
Full
80.0
85.0
71.4
58.9
73.7
7× orig. ens.
Full
76.9
85.9
75.3
55.0
73.3
Table 4: Performance of single-prompt methods, ensemble methods, and human annotators on test set (n=150) in full and simplified coarse label schema. All values are F-score.
Question
Multi-label %
Total
Labels
Q1 – Category
29.2%
17,717
18
Q2 – Group size
6.6%
4,014
3
Q3 – Frequency
1.8%
1,076
4
Q4 – Physical act.
2.5%
1,511
4
Table 5: Multi-label entity distribution across questions.
Q1 Category
n
Q1
Q2
Q3
Q4
Creative/Artistic
33
93/95
85/91
90/94
51/87
Professional
27
77/88
91/96
70/81
63/77
Sports/Physical
24
82/93
81/89
72/85
76/90
Administrative
21
85/88
95/96
76/79
84/83
Nature-related
19
79/92
75/86
60/71
58/72
General social
12
75/88
92/97
47/82
0/65
Table 6: Q1–Q4 reliability conditioned by entity category in Q1, showing both model and human agreement rates. Format: Model% / Human%. Colors: ≥ 75% , 50–74% , < 50% (based on lower score).
Perfect agreement (0%)
19%
Low disag. (<25%)
44%
Moderate disag. (25–50%)
30%
High disag. (>50%)
7%
Table 7: Degrees of model–human disagreement.
Appendix figures & tables5 assets
Supplementary material from the paper’s appendix.
Appendix
Annotator Pair
Q1
Q2
Q3
Q4
Average
Pairwise Cohen’s Kappa – Evaluation Set (n=50)
Annotator 1 vs 2
0.800
0.806
0.667
0.721
0.749
Annotator 1 vs 3
0.753
0.743
0.725
0.711
0.733
Annotator 1 vs 4
0.753
0.767
0.524
0.660
0.676
Annotator 2 vs 3
0.684
0.753
0.677
0.688
0.701
Annotator 2 vs 4
0.697
0.848
0.651
0.754
0.737
Appendix
Table 8: Inter-annotator agreement metrics across evaluation (n=50) and test (n=150) sets.
Q1 – Category
Q2 – Group Size
Label
n
%
Label
n
%
Administrative
11,844
19.5
Large group
53,574
88.3
Professional
10,830
17.9
Small group
4,889
8.1
General Social
7,744
12.8
Alone
4,840
8.0
Creative
7,396
12.2
Data error
853
1.4
Sports
7,328
12.1
Not definable
654
1.1
Appendix
Table 9: Distribution across 60,647 unique entities for all four questions.
Hobbies
Organizations
Total
Label
Count
%
Count
%
Count
%
Q2 – Group Size
Large group
55,252
12.9
198,318
96.1
253,570
39.9
Alone
186,679
43.4
512
0.2
187,191
29.4
Small group
174,877
40.7
4,104
2.0
178,981
28.1
Not definable
12,232
2.8
1,140
0.6
13,372
2.1
Appendix
Table 10: Mention-weighted distribution (355,648 total mentions) for Q2–Q4 by entity type.
Hobbies
Organizations
Total
Category
Count
%
Count
%
Count
%
Creative/Artistic
97,180
36.3
16,639
6.3
113,819
21.4
Nature-related
88,174
32.9
3,880
1.5
92,054
17.3
Sports/Physical
46,269
17.3
15,390
5.8
61,659
11.6
General Social Group
1,621
0.6
50,089
19.0
51,710
9.7
Professional/Work
1,811
0.7
32,344
12.3
34,155
6.4
Appendix
Table 11: Q1 category distribution weighted by mention frequency (355,648 total mentions).
Rank
Entity
Model Disagr
Human Disagr
1
Loimaa Co-op Bank ( Loimaan KOP )
100.0%
66.7%
2
Folk dance ( tanhu )
100.0%
50.7%
3
Poor relief fund ( Vaivaiskassa )
100.0%
66.7%
4
Military regiment abbr. ( 2.KKK/KKR )
91.7%
75.0%
5
Association abbr. ( KTV )
87.5%
25.0%
6
Summer cottage life ( kesämökkielämä )
79.2%
56.2%
Appendix
Table 12: Model and human disagreement over the 150 test set entities.