GRADUATE MONITORING AND STATISTICAL ANALYSIS
Employment of the 2024–2025 graduating class: an extended analytical report
“Silk Road” International University of Tourism and Cultural Heritage
1. Executive summary
Figure 1. Key indicators (based on HEMIS statistics and the individual graduate list)
This report draws on two sources: HEMIS summary statistics for the 2024–2025 academic year and an individual
employment list of 342 graduates (as of 03.11.2026). The two sources reconcile fully: both the totals and the
distribution by economic sector are identical. Main findings:
 Coverage. Of 415 graduates, 62 are foreign nationals. Of the remaining 353, 342 (96.9%) are covered by
monitoring; 11 bachelor graduates are not reflected in the data.
 Activity. 256 graduates (74.9%; 95% confidence interval 70.0–79.2%) are in work or study. Employment
alone covers 221 (64.6%). Excluding those on mandatory leave (51), activity reaches 88.0%.
 No recorded unemployment. The “temporarily unemployed” category is empty. A reason is given for each
of the 86 graduates not working: childcare leave (48), left abroad (18), illness (17), parental leave (2),
military service (1).
 The gender gap is driven by leave. Activity is 65.5% for women and 88.5% for men (p < 0.001).
Excluding inactive graduates, the figures are 86.9% and 89.1% and the difference is no longer significant (p
= 0.56).
 High sector concentration. 58.8% of employed graduates work in services and 24.9% in education. The
Herfindahl–Hirschman index is 3,755.
 State-grant graduates tend to continue studying. Grant: 25.7%, contract: 6.0% (p < 0.001; odds ratio
5.4).
 Timing. 52.9% of employed graduates were already working before 1 July 2025 (part-time 67.3%, full-time
41.5%). Among the 104 who started after graduation, the median wait was 4.1 months; 34.6% were placed
within 3 months and 66.3% within 6.
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 Migration risk. 18 graduates (5.3%) left the country: 7.0% of bachelors versus 1.8% of masters (p = 0.042);
13 of the 18 are men.
Key conclusion: the focus should be less on whether graduates find work and more on the structure of
employment: women’s social leave, labour migration, over-reliance on one sector (services) and the quality of data
recording.
2. Data sources and methodology
2.1. Sources used

2.2. Indicators and calculation

2.3. Limits of interpretation
 The data are a single snapshot (3 November 2026) and do not track graduates over time.
 Gender is available only in the HEMIS summary; the individual list has no gender column, so gender was
not inferred from names.
 Employer type and position groups were classified approximately from keywords in names. Precise
classification requires the employer tax ID (STIR) and a position classifier.
 For the timing analysis the graduation date was assumed to be 30 June 2025 (end of the academic year); the
list has no exact graduation date.
 Some groups are small (7–14 graduates), so group- and specialty-level differences should be read as
preliminary signals.
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3. Graduate cohort and monitoring coverage
Figure 2. Monitoring coverage and composition of the 342 monitored graduates

The master’s cohort stands out in two ways: 61 graduates (35.1%) are foreign nationals, almost all of them (59) on
grants; and 90.3% of domestic master’s graduates are women (102/113). Both facts matter for interpreting the
employment differences below.
Data quality note. Bachelor graduates: 241 - 1 (foreign) - 229 = 11 graduates are missing from the list. Their
status is unknown. Identifying them would bring coverage to 100% and may change the indicators.
4. Overall employment indicators

On the raw figures, bachelors (79.0%) outperform masters (66.4%), and the difference is statistically significant
(χ² = 6.45; p = 0.011). But this reflects the share of inactive graduates rather than labour-market opportunities:
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25.7% of masters and 9.6% of bachelors are on parental or childcare leave. Once inactive graduates are excluded,
masters (89.3%) are slightly ahead of bachelors (87.4%), and the difference is not significant (p = 0.66).
A second important fact is that the “temporarily unemployed” category is empty. This may mean unemployment
is genuinely very low, or that jobless graduates are being recorded under “illness” or “left abroad”. Independent
verification of the status of the 35 graduates “in process” is recommended.
5. Analysis by economic sector
Figure 3. Placement of the 256 economically active graduates by sector
 Services — 130 graduates: 50.8% of the economically active and 58.8% of the employed. 72.7% of
employed bachelors (109/150) work in this sector.
 Education systems (public education 33, higher 11, secondary vocational 8, preschool 3) total 55 graduates,
or 24.9% of the employed. Public education is also the largest destination for masters: 28 graduates (39.4%
of employed masters), all women.
 All other sectors (public administration 7, banking and finance 5, industry 4, transport 3, agriculture 3 and
others) together account for only 16.3% of the employed.
 Concentration. The sector distribution of employed graduates gives HHI = 3,755 (on a 10,000 scale). By
the conventional reading, values above 2,500 indicate high concentration. This is natural for a tourism
university but increases sensitivity to shifts in service-sector demand.
Classification inconsistency. The list shows 31 graduates whose employer is “self-employed” or a sole
proprietorship. Of these, 23 are filed under “Services”, 6 under “Entrepreneurship (in specialty)” and 2 elsewhere.
HEMIS therefore reports 7 entrepreneurs, understating actual entrepreneurship/self-employment (31 graduates,
14.0%).
Field match of 99.2% (254/256) is very high. The list records tourism, MBA and management master’s
graduates working in public education (schools): of the 28 master’s graduates, 7 studied tourism and hospitality, 7
MBA and 6 management. In such cases a spot check of how the match criterion and the position (for example,
foreign-language teacher) relate to the specialty is recommended.
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6. Analysis by gender
Figure 4. Employment structure by gender and degree level
Gender produces the largest difference: women’s economic activity is 65.5% (133/203) against 88.5% for men
(123/139); the gap is 23.0 percentage points (χ² = 23.13; p < 0.001; odds ratio 0.25). Among bachelors the pattern
is the same: 68.3% versus 87.5% (p < 0.001).
The main source of the gap is social leave. Of the 51 inactive graduates, 50 are women: inactivity is 24.6% among
women (50/203) and 0.7% among men (1/139). Excluding inactive graduates, women’s activity is 86.9%
(133/153) and men’s 89.1% (123/138); the difference is not significant (χ² = 0.33; p = 0.56). In other words,
women who were not on leave achieved almost the same employment level as men.
Figure 5. Graduates not working (86): reasons and gender
Risks also differ by gender in the “in process” group: 13 of the 18 graduates who left the country are men, while
15 of the 17 not working due to illness are women. For men the main risk is labour migration; for women it is the
motherhood period.
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7. Degree level, funding type and study form
Figure 6. Employment structure by degree level and funding type (HEMIS)

Funding type. Overall activity is almost identical for grant (74.3%) and contract (75.0%) graduates (p = 0.91).
The internal composition differs sharply, however: one third of grant bachelors (33.3%) continued studying,
compared with 7.9% of contract bachelors. Lower employment among grant bachelors (43.1% versus 71.9%)
therefore reflects an academic-pathway choice rather than weaker outcomes.
Study form. Part-time graduates have 80.0% activity (100/125) versus 71.9% for full-time (156/217); the
difference is not significant at the 5% level (χ² = 2.77; p = 0.096). The comparison is somewhat mixed because all
masters, who have high inactivity, are in the full-time group. Most part-time graduates (67.3%) were already
working before graduation, so what is measured for them is retention of an existing job rather than job placement.
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8. Monitoring by specialty and study group
Figure 7. Economic activity by specialty (active / total)
Strongest results: Guiding and translation 100% (14/14), Marketing (tourism marketing) 85.0% (17/20), Tourism
(activity areas) 81.5% (88/108), Management (event management) 78.4% (29/37). Weakest results: Media and
communication in tourism 55.6% (5/9), Archaeology (master) 57.1% (4/7), Museology (master) 60.0% (6/10),
History and theory of architecture and Management (master) 62.5%, Applied philology 63.6% (7/11). Because
samples are small, confidence intervals are wide; the results are best used as signals for targeted follow-up.
Figure 8. Economic activity across the 23 study groups (active / total)
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The six groups below 65%: Man-124M — 50.0% (7/14), MBA-124M — 53.8% (7/13), Media-121 — 55.6%
(5/9), Arch-124M — 57.1% (4/7), MS-124M — 60.0% (6/10), Lang-121 — 63.6% (7/11). In all of them the
cause is childcare or parental leave, illness or having left the country; none has a graduate recorded as
“temporarily unemployed”. In MBA-124M, for example, 5 of the 6 inactive graduates are on childcare leave.
Activity versus net employment. Guide-121 (100%), Smart-121 (91.7%) and Tour-121 (88.9%) lead on activity,
but only because 5–7 graduates in each continued their studies. The employed-only share in these groups is 64.3%,
50.0% and 50.0%. The Career Center should track “work” and “study” pathways separately.
9. Employment timing
Figure 9. Job start dates: monthly distribution and cumulative curve
Start dates are available for all 221 employed graduates. 117 of them (52.9%) started before 1 July 2025, that is,
were already working at graduation: 66 of 98 part-time graduates (67.3%) and 51 of 123 full-time graduates
(41.5%). A large share of employment is therefore not placement delivered by the university but employment held
during study.
For the 104 who started after graduation, the median wait is 4.1 months; 7.7% were placed within 1 month,
34.6% within 3 months, 66.3% within 6 months and 97.1% within 12 months. Hiring peaked in September 2025
(19 graduates) and between October and February; activity was low in March–June 2026 (2–4 graduates a month).
With only one in three graduates placed in the first three months, services that support placement before
graduation need strengthening.
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10. Employers, positions and continuing study
Figure 10. Employer type and position groups (221 employed; approximate classification by name)
Employer type. The private sector (LLCs, joint-stock companies, farms) accounts for 122 graduates (55.2%), the
public sector 56 (25.3%), self-employment/sole proprietorship 31 (14.0%) and foreign-capital or overseas
companies 12 (5.4%). Self-employment is especially common among bachelors: 26 graduates (17.3% of
employed bachelors).
Positions. The largest groups are manager, specialist and office staff (59; 26.7%) and teacher/tutor (55; 24.9%).
Clearly tourism and hospitality occupations (guide, translator, tour operator — 16; hotel and catering — 11)
number 27 (12.2%) by job title, so a large part of those working in services hold general management, sales and
support roles. The title “director” appears 10 times; these may be owners of their own businesses and should be
verified.
Table 1. Recurring employers (employed graduates)

By name there are roughly 181 distinct employers, and 164 of them (90.6%) employ a single graduate.
Employment is thus widely dispersed, yet no employer reaches “anchor partner” level; this is an opportunity to
extend strategic cooperation agreements.
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Figure 11. Destinations of graduates continuing their studies
35 graduates (10.2%) are continuing their studies: 31 bachelors and 4 masters (3 of them in doctoral programmes).
Most stay at the own university (15; 42.9%), 11 (31.4%) study at other domestic universities and 9 (25.7%)
abroad (China 4, Italy 2, UK 2, Latvia 1). 3.9% of bachelor graduates (9/229) are studying abroad.
11. Statistical tests
Figure 12. Economic activity rate: groups and 95% Wilson confidence intervals
Table 2. Tests of differences between groups

Note: χ² is Pearson’s test without continuity correction, 1 degree of freedom; * Fisher’s exact test also gives p = 0.042. OR = odds ratio.
The tests are descriptive: several comparisons were run at once, so borderline results (p ≈ 0.04–0.05) should be
interpreted with caution, and observational data do not support causal conclusions.
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12. Risks, opportunities and recommendations
Table 3. Main risks and supporting evidence

Table 4. Proposed monitoring indicators (targets may be adjusted by the Center)

Appendix A. Monitoring by study group

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Reason given — graduates not working whose reason is recorded (leave, illness, abroad and others). Active = work + study.
Appendix B. Monitoring by specialty

Appendix C Statistical methods
 Wilson confidence interval (95%) for proportions, more reliable than the normal approximation in small
samples.
 Pearson χ² (1 degree of freedom, no correction) and Fisher’s exact test for 2×2 tables; odds ratio (OR) as
the effect size.
 Herfindahl–Hirschman index: HHI = Σ(sᵢ)² × 10,000, where sᵢ is the sector’s share among employed
graduates (221, excluding those continuing studies).
 Cumulative timing: for the 104 graduates who started work after 1 July 2025, months from graduation to job
s t a r t ( d a y s