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Gecikmeli Güvenlik Göstergeleriyle İş Kazalarının Tahminlemesi: 21. Yüzyılda Sosyal Güvenlik Dönüşümüne Yönelik Perspektifler

Yıl 2025, Sayı: Özel Sayı, 299 - 346, 10.06.2025

Gökhan Tuna

https://doi.org/10.21441/sosyalguvence.1682358

Öz

21. yüzyıl, sosyal güvenlik sistemlerinin dayanıklılığını ve uyum kabiliyetini zorlayan karmaşık ve gelişen riskleri beraberinde getirmiştir. Bunlar arasında, iş kazaları ve iş göremezlik durumları, iş gücü istikrarı, gelir güvenliği ve uzun vadeli refah açısından, kalıcı tehditler oluşturmaya devam etmektedir. Teknolojik dönüşümler işin doğasını değiştirirken ve küresel krizler—örneğin COVID-19 pandemisi—işyeri koruma mekanizmalarındaki kırılganlıkları açığa çıkarırken, iş risklerinin yönetim çerçevelerini yeniden değerlendirme ve güçlendirme ihtiyacı giderek daha acil hale gelmektedir. Bu çalışma, mesleki risk yönetimini sosyal güvenlik çerçevelerinin modernizasyonu bağlamında konumlandırmaktadır. Dijital araçların ve tahminleme analitiklerin güvenlik izleme sistemlerine entegrasyonunu savunarak, ortaya çıkan iş gücü piyasası dinamiklerine daha duyarlı hale gelinmesini önermektedir, iş sağlığı ve güvenliğinde gecikmeli göstergelerin özellikleri incelemekte olup, sırasıyla reaktif ve proaktif çözümleri içermektedir. Türkiye’de 2013-2023 yılları arasındaki iş kazalarına ilişkin veriler kullanılarak zaman serisi analizi, korelasyon analizi, Granger nedensellik testleri ve tahmin modelleri geliştirilmiştir. Gecikmeli göstergeler ile kazalar ve ölümler gibi sonuçlar arasındaki ilişkileri ve bunların etkileri analiz edilmiştir. Sonuçlar, işyerinde kazaları en aza indirmek için önleyici eylemlerin alınmasının önemini vurgulamakta ve gecikmeli göstergelerin gelecekteki güvenlik girişimlerine rehberlik etmek için nasıl kullanılabileceğini göstermektedir. Gecikmeli göstergeler, proaktif bir şekilde kullanıldığında tahmin araçları olarak da işlev görebilir. Bu bulgular, iş sağlığı ve güvenliği sonuçlarını iyileştirmek için sürekli izlemenin gerekliliğini ve hedefe yönelik müdahalelerin önemini ortaya koymaktadır. Ampirik bulguları çağdaş politika zorluklarıyla—yeni istihdam modellerine uyum sağlama ve eşitsizlikleri azaltma gibi—ilişkilendirerek, çalışmanın dayanıklı, kapsayıcı ve geleceğe hazır sosyal koruma sistemlerinin oluşturulmasına yönelik tartışmalara katkı sağlamasını amaçlamaktadır.

Anahtar Kelimeler

Gecikmeli Güvenlik Göstergeleri İş Kazaları İş Sağlığı ve Güvenliği Tahmini Modelleme

Kaynakça

  • Aggarwal, C. C. (2015). Outlier Analysis (2nd ed.). Springer.
  • Akgündüz, Y. E., & Torun, H. (2018). The effects of workplace injuries on labor market outcomes: Evidence from Türkiye. Labour Economics, 55, 1–14.
  • Aydın, G., & Kaya, İ. (2020). Forecasting seasonal influenza incidence using composite models. Computer Methods and Programs in Biomedicine, 185, 105151.
  • Bayramlar, O., Ezirmik, E., İşsever, H., & Bayramlar, Z. (2019). Standardization of the numbers of work accidents, occupational diseases and mortality rates according to Social Security Institution’s 2010-2015 years data based upon cities. Journal of Istanbul Faculty of Medicine, 82(1), 29–39.
  • Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley.
  • Box-Steffensmeier, J. M., & Tomlinson, A. R. (2000). Fractional integration methods in political science. Electoral Studies, 19 (1), 63–80. https://doi.org/10.1016/S0261-3794 (99)00013-7
  • Centers for Disease Control and Prevention (CDC). (2021). NIOSH: National Institute for Occupational Safety and Health. https://www.cdc.gov/niosh/about/default.html
  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (3rd ed.). Routledge.
  • Çelik, S., & Başar, A. (2020). Veri Ön İşleme Tekniklerinin Makine Öğrenmesi Performansına Etkisi. Bilişim Teknolojileri Dergisi, 13(2), 123-134.
  • Dale, B. G., Glencross, M. J., & Stapleton, O. (2017). Understanding and applying health and safety performance indicators. Health Manpower Management, 26(6), 245–253.
  • Demirbilek, S. (2017). Türkiye’de iş kazalarının ekonomik ve sosyal boyutları. Çalışma ve Toplum Dergisi, 52, 45-68. https://www.calismatoplum.org/makale/turkiyede-is-kazalarinin-ekonomik-ve-sosyal-boyutlari
  • Dyreborg, J. (2009). The Causal Relation Between Lead and Lag Indicators. Safety Science. 47(4). 474-475.
  • European Agency for Safety and Health at Work. (2021). Why is OSH important? Occupational Safety and Health Wiki.
  • Eurostat. (2008). NACE Rev. 2: Statistical classification of economic activities in the European Community. Luxembourg: Office for Official Publications of the European Communities.
  • Eurostat. (2024). Accidents at work statistics. European Statistical Office. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Accidents_at_work_statistics.
  • Flin, R., Marshall, S., Martin, L., & Fleck, R. (2000). Measuring safety climate: Identifying the common features. Safety Science, 34 (1–3), 177–192. https://doi.org/10.1016/S0925-7535 (00)00017-6
  • Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.
  • Gürcanli, G. E., & Müngen, U. (2013). Analysis of construction accidents in Türkiye and responsible parties. Industrial Health, 51(6), 581-595. https://doi.org/10.2486/indhealth.2012-0139
  • Hale, A. R., & Hovden, J. (1998). Management and culture: The third age of safety. In A. Feyer & A. Williamson (Eds.), Occupational injury: Risk, prevention and intervention (pp. 129-166). Taylor & Francis.
  • Goh, Y. M., & Zainuddin, N. R. (2017). A review of research trends in the study of construction safety performance indicators. Safety Science, 98, 130–141. https://doi.org/10.1016/j.ssci.2017.06.009Hallowell, M. R., et al. (2023). Severity-based lagging indicator for safety performance measurement. Professional Safety, 68(4), 24-31.
  • Hasle, P. F. (2014). Safety performance indicators-Useful tools for safety management. Safety Science, 62, 12–18. https://doi.org/10.1016/j.ssci.2013.07.006
  • Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.). Springer.
  • Hinze, J., Petersen, S., & Fleury, M. R. (2013). Factors contributing to falling from heights in construction. Journal of Construction Engineering and Management, 139(5), 571–578.
  • Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression (3rd ed.). Wiley.
  • Hyndman, R. J., & Athanasopoulos, G. (2021). Forecasting: Principles and Practice (3rd ed.). OTexts.
  • International Labour Organization (ILO). (2023). World Day for Safety and Health at Work 2025: Global report. ILO Publications.
  • Işık, V., & Yılmaz Işıkhan, S. (2024). Trend analysis of occupational accidents during 2013–2020 based on various characteristics in Türkiye. Workplace Health & Safety, 72(12).
  • Kaya, U., & Çebi, Y. (2019). İş Kazalarının Korelasyon Analizi ile İncelenmesi. Endüstri Mühendisliği Dergisi, 30(2), 89-102.
  • Khanzode, V. V., Maiti, J., & Ray, P. K. (2012). Occupational injury and accident research: A comprehensive review. Safety Science, 50(5), 1355-1367. https://doi.org/ doi:10.1016/j.ssci.2011.12.015.
  • Kuhn, M., & Johnson, K. (2013). Applied predictive modeling. Springer.
  • Lingard, H., & Rowlinson, S. (2005). Occupational health and safety in construction project management. Taylor & Francis.
  • Little, R. J., & Rubin, D. B. (2019). Statistical Analysis with Missing Data (3rd ed.). Wiley.
  • Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
  • Makin, A. M., & Winder, C. (2008). A review of the strengths and limitations of commonly used health and safety performance indicators. Safety Science, 46(5), 656-658.
  • Manuele, F. A. (2009). Leading & lagging indicators. Professional Safety, 54(12), 28-33.
  • Myers, A., Ahn, S., Jin, Y., & Schafer, W. D. (2010). Correlational research . In N. J. Salkind (Ed.), Encyclopedia of research design (pp. 251–254). SAGE Publications.
  • Montgomery, D. C., Peck, E. A., & Vining, G. G. (2012). Introduction to Linear Regression Analysis (5th ed.). Wiley.
  • Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to linear regression analysis (6th ed.). Wiley.
  • Neal, A., & Griffin, M. A. (2006). A study of the lagged relationships among safety climate, safety motivation, safety behavior, and accidents at work. Journal of Applied Psychology, 91 (4), 849–858. https://doi.org/10.1037/0021-9010.91.4.849
  • Özdemir, H., & Yılmaz, E. (2018). Türkiye’de iş kazalarının sosyo-ekonomik etkileri ve tazminat süreçleri. Çalışma ve Toplum Dergisi, 59(4), 123-145.
  • Özkan, Ö., & Yilmaz, F. (2018). Social security and occupational health and safety in Türkiye: A comparative analysis. Journal of Social Security, 8(2), 123-140.
  • Özmen, A., & Yılmaz, E. (2018). Türkiye’de Trafik Kazalarının Zaman Serisi Analizi. İstatistik ve Uygulamalı Bilimler Dergisi, 4(1), 45-56.
  • Pawłowska, Z. (2015). Using lagging and leading indicators for the evaluation of occupational safety and health performance in industry. International Journal of Occupational Safety and Ergonomics, 21(3), 284-290.
  • Reason, J. (1997). Managing the risks of organizational accidents. Ashgate Publishing.
  • Seyyar, A. (2015). Türkiye’de sosyal güvenlik sistemi ve iş kazaları. Ankara: İmaj Yayınevi.
  • Shea, T., De Cieri, H., Donohue, R., Cooper, B., & Sheehan, C. (2016). Leading and lagging indicators of occupational health and safety: The moderating role of safety leadership. Accident Analysis & Prevention, 92, 130-138.
  • Sosyal Güvenlik Kurumu (SGK). (n.d.). 2013-2023 yılı sigortalı ve iş yeri iş kazaları ve meslek hastalıkları istatistik yıllıkları.
  • Şimşek, M., & Özdemir, A. (2021). Türkiye’de İş Kazaları ve Ekonomik Göstergeler Arasındaki Nedensellik İlişkisi. Sosyal Bilimler Dergisi, 15(3), 210-225.
  • T.C. Resmi Gazete. (2012). İş Sağlığı ve Güvenliği Kanunu (Kanun No. 6331). Resmi Gazete, Sayı: 28339, 30 Haziran 2012. https://www.resmigazete.gov.tr/eskiler/2012/06/20120630-1.htm
  • Taylor, R. (1990). Interpretation of the Correlation Coefficient: A Basic Review. Journal of Diagnostic Medical Sonography, 6(1), 35-39.
  • Underwriters Laboratories. (2013). Using leading and lagging safety indicators to manage workplace health and safety risk. https://code-authorities.ul.com/wp-content/uploads/sites/40/2015/02/UL_WP_Final_Using-Leading-and-Lagging-Safety-Indicators-to-Manage-Workplace-Health-and-Safety-Risk_V7-LR1.pdf
  • United Nations. (2023). Sustainable Development Goal 8: Decent work and economic growth.
  • World Health Organization (WHO). (2023). Occupational health.
  • Yorio, P. L., Haas, E. J., Bell, J. L., & Moore, S. M. (2020). Lagging or leading? Exploring the temporal relationship among lagging indicators in mining establishments 2006–2017. Journal of Safety Research, 72, 147-157.
  • Zhang, Y., & Zhou, Q. (2021). A review of machine learning applications in occupational safety: Approaches, advantages, and challenges. Safety Science, 142, 105368.
  • Zhou, Q., Fang, D., & Wang, X. (2008). A method to identify key variables in construction safety management. Journal of Safety Research, 39(3), 269–279.
  • Zwetsloot, G. I. J. M., Scheppingen, A. R. V., Starren, A., & Bos, E. L. (2013). The development of a framework to improve health and safety performance measurement: An explorative study. Safety Science, 55, 122–132. https://doi.org/10.1016/j.ssci.2013.01.015

Predictive Modeling Of Work Accidents Using Lagging Safety Indicators: Perspectives On Social Security Transformation In The 21st Century

Yıl 2025, Sayı: Özel Sayı, 299 - 346, 10.06.2025

Gökhan Tuna

https://doi.org/10.21441/sosyalguvence.1682358

Öz

The 21st century has introduced complex and evolving risks that challenge the resilience and adaptability of social security systems. Among these, work accidents and occupational disabilities continue to pose persistent threats to labor force stability, income security, and long-term well-being. As technological transformations reshape the nature of work and global crises—such as the COVID-19 pandemic—expose vulnerabilities in workplace protections, the need to reassess and strengthen occupational risk frameworks becomes increasingly urgent. This article positions occupational risk management within the broader context of modernizing social security frameworks. It advocates for the integration of digital tools and predictive analytics into safety monitoring systems to enhance responsiveness to emerging labor market Dynamics, it examines the characteristics of lagging indicators in occupational health and safety, and includes reactive and proactive solutions, respectively. Using data on work accidents in Türkiye from 2013 to 2023, time series analysis, correlation analysis, Granger causality tests, and predictive models were developed. The relationships between lagging indicators and outcomes such as accidents and fatalities and their effects analyzed. The results underscore the significance of taking preventive actions to minimize accidents in the workplace and illustrate how lagging indicators can be utilized to guide upcoming safety initiatives. Lagging indicators can also serve as predictive tools when used proactively. These findings highlight the need for continuous monitoring and the importance of targeted interventions to improve occupational health and safety outcomes. By linking empirical findings to contemporary policy challenges—such as adapting to new employment models and mitigating inequalities—the study contributes to discussions on building resilient, inclusive, and future-ready social protection systems.

Anahtar Kelimeler

Lagging Safety Indicators Work Accidents Occupational Health and Safety Predictive Modelling

Kaynakça

  • Aggarwal, C. C. (2015). Outlier Analysis (2nd ed.). Springer.
  • Akgündüz, Y. E., & Torun, H. (2018). The effects of workplace injuries on labor market outcomes: Evidence from Türkiye. Labour Economics, 55, 1–14.
  • Aydın, G., & Kaya, İ. (2020). Forecasting seasonal influenza incidence using composite models. Computer Methods and Programs in Biomedicine, 185, 105151.
  • Bayramlar, O., Ezirmik, E., İşsever, H., & Bayramlar, Z. (2019). Standardization of the numbers of work accidents, occupational diseases and mortality rates according to Social Security Institution’s 2010-2015 years data based upon cities. Journal of Istanbul Faculty of Medicine, 82(1), 29–39.
  • Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley.
  • Box-Steffensmeier, J. M., & Tomlinson, A. R. (2000). Fractional integration methods in political science. Electoral Studies, 19 (1), 63–80. https://doi.org/10.1016/S0261-3794 (99)00013-7
  • Centers for Disease Control and Prevention (CDC). (2021). NIOSH: National Institute for Occupational Safety and Health. https://www.cdc.gov/niosh/about/default.html
  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (3rd ed.). Routledge.
  • Çelik, S., & Başar, A. (2020). Veri Ön İşleme Tekniklerinin Makine Öğrenmesi Performansına Etkisi. Bilişim Teknolojileri Dergisi, 13(2), 123-134.
  • Dale, B. G., Glencross, M. J., & Stapleton, O. (2017). Understanding and applying health and safety performance indicators. Health Manpower Management, 26(6), 245–253.
  • Demirbilek, S. (2017). Türkiye’de iş kazalarının ekonomik ve sosyal boyutları. Çalışma ve Toplum Dergisi, 52, 45-68. https://www.calismatoplum.org/makale/turkiyede-is-kazalarinin-ekonomik-ve-sosyal-boyutlari
  • Dyreborg, J. (2009). The Causal Relation Between Lead and Lag Indicators. Safety Science. 47(4). 474-475.
  • European Agency for Safety and Health at Work. (2021). Why is OSH important? Occupational Safety and Health Wiki.
  • Eurostat. (2008). NACE Rev. 2: Statistical classification of economic activities in the European Community. Luxembourg: Office for Official Publications of the European Communities.
  • Eurostat. (2024). Accidents at work statistics. European Statistical Office. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Accidents_at_work_statistics.
  • Flin, R., Marshall, S., Martin, L., & Fleck, R. (2000). Measuring safety climate: Identifying the common features. Safety Science, 34 (1–3), 177–192. https://doi.org/10.1016/S0925-7535 (00)00017-6
  • Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.
  • Gürcanli, G. E., & Müngen, U. (2013). Analysis of construction accidents in Türkiye and responsible parties. Industrial Health, 51(6), 581-595. https://doi.org/10.2486/indhealth.2012-0139
  • Hale, A. R., & Hovden, J. (1998). Management and culture: The third age of safety. In A. Feyer & A. Williamson (Eds.), Occupational injury: Risk, prevention and intervention (pp. 129-166). Taylor & Francis.
  • Goh, Y. M., & Zainuddin, N. R. (2017). A review of research trends in the study of construction safety performance indicators. Safety Science, 98, 130–141. https://doi.org/10.1016/j.ssci.2017.06.009Hallowell, M. R., et al. (2023). Severity-based lagging indicator for safety performance measurement. Professional Safety, 68(4), 24-31.
  • Hasle, P. F. (2014). Safety performance indicators-Useful tools for safety management. Safety Science, 62, 12–18. https://doi.org/10.1016/j.ssci.2013.07.006
  • Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.). Springer.
  • Hinze, J., Petersen, S., & Fleury, M. R. (2013). Factors contributing to falling from heights in construction. Journal of Construction Engineering and Management, 139(5), 571–578.
  • Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression (3rd ed.). Wiley.
  • Hyndman, R. J., & Athanasopoulos, G. (2021). Forecasting: Principles and Practice (3rd ed.). OTexts.
  • International Labour Organization (ILO). (2023). World Day for Safety and Health at Work 2025: Global report. ILO Publications.
  • Işık, V., & Yılmaz Işıkhan, S. (2024). Trend analysis of occupational accidents during 2013–2020 based on various characteristics in Türkiye. Workplace Health & Safety, 72(12).
  • Kaya, U., & Çebi, Y. (2019). İş Kazalarının Korelasyon Analizi ile İncelenmesi. Endüstri Mühendisliği Dergisi, 30(2), 89-102.
  • Khanzode, V. V., Maiti, J., & Ray, P. K. (2012). Occupational injury and accident research: A comprehensive review. Safety Science, 50(5), 1355-1367. https://doi.org/ doi:10.1016/j.ssci.2011.12.015.
  • Kuhn, M., & Johnson, K. (2013). Applied predictive modeling. Springer.
  • Lingard, H., & Rowlinson, S. (2005). Occupational health and safety in construction project management. Taylor & Francis.
  • Little, R. J., & Rubin, D. B. (2019). Statistical Analysis with Missing Data (3rd ed.). Wiley.
  • Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
  • Makin, A. M., & Winder, C. (2008). A review of the strengths and limitations of commonly used health and safety performance indicators. Safety Science, 46(5), 656-658.
  • Manuele, F. A. (2009). Leading & lagging indicators. Professional Safety, 54(12), 28-33.
  • Myers, A., Ahn, S., Jin, Y., & Schafer, W. D. (2010). Correlational research . In N. J. Salkind (Ed.), Encyclopedia of research design (pp. 251–254). SAGE Publications.
  • Montgomery, D. C., Peck, E. A., & Vining, G. G. (2012). Introduction to Linear Regression Analysis (5th ed.). Wiley.
  • Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to linear regression analysis (6th ed.). Wiley.
  • Neal, A., & Griffin, M. A. (2006). A study of the lagged relationships among safety climate, safety motivation, safety behavior, and accidents at work. Journal of Applied Psychology, 91 (4), 849–858. https://doi.org/10.1037/0021-9010.91.4.849
  • Özdemir, H., & Yılmaz, E. (2018). Türkiye’de iş kazalarının sosyo-ekonomik etkileri ve tazminat süreçleri. Çalışma ve Toplum Dergisi, 59(4), 123-145.
  • Özkan, Ö., & Yilmaz, F. (2018). Social security and occupational health and safety in Türkiye: A comparative analysis. Journal of Social Security, 8(2), 123-140.
  • Özmen, A., & Yılmaz, E. (2018). Türkiye’de Trafik Kazalarının Zaman Serisi Analizi. İstatistik ve Uygulamalı Bilimler Dergisi, 4(1), 45-56.
  • Pawłowska, Z. (2015). Using lagging and leading indicators for the evaluation of occupational safety and health performance in industry. International Journal of Occupational Safety and Ergonomics, 21(3), 284-290.
  • Reason, J. (1997). Managing the risks of organizational accidents. Ashgate Publishing.
  • Seyyar, A. (2015). Türkiye’de sosyal güvenlik sistemi ve iş kazaları. Ankara: İmaj Yayınevi.
  • Shea, T., De Cieri, H., Donohue, R., Cooper, B., & Sheehan, C. (2016). Leading and lagging indicators of occupational health and safety: The moderating role of safety leadership. Accident Analysis & Prevention, 92, 130-138.
  • Sosyal Güvenlik Kurumu (SGK). (n.d.). 2013-2023 yılı sigortalı ve iş yeri iş kazaları ve meslek hastalıkları istatistik yıllıkları.
  • Şimşek, M., & Özdemir, A. (2021). Türkiye’de İş Kazaları ve Ekonomik Göstergeler Arasındaki Nedensellik İlişkisi. Sosyal Bilimler Dergisi, 15(3), 210-225.
  • T.C. Resmi Gazete. (2012). İş Sağlığı ve Güvenliği Kanunu (Kanun No. 6331). Resmi Gazete, Sayı: 28339, 30 Haziran 2012. https://www.resmigazete.gov.tr/eskiler/2012/06/20120630-1.htm
  • Taylor, R. (1990). Interpretation of the Correlation Coefficient: A Basic Review. Journal of Diagnostic Medical Sonography, 6(1), 35-39.
  • Underwriters Laboratories. (2013). Using leading and lagging safety indicators to manage workplace health and safety risk. https://code-authorities.ul.com/wp-content/uploads/sites/40/2015/02/UL_WP_Final_Using-Leading-and-Lagging-Safety-Indicators-to-Manage-Workplace-Health-and-Safety-Risk_V7-LR1.pdf
  • United Nations. (2023). Sustainable Development Goal 8: Decent work and economic growth.
  • World Health Organization (WHO). (2023). Occupational health.
  • Yorio, P. L., Haas, E. J., Bell, J. L., & Moore, S. M. (2020). Lagging or leading? Exploring the temporal relationship among lagging indicators in mining establishments 2006–2017. Journal of Safety Research, 72, 147-157.
  • Zhang, Y., & Zhou, Q. (2021). A review of machine learning applications in occupational safety: Approaches, advantages, and challenges. Safety Science, 142, 105368.
  • Zhou, Q., Fang, D., & Wang, X. (2008). A method to identify key variables in construction safety management. Journal of Safety Research, 39(3), 269–279.
  • Zwetsloot, G. I. J. M., Scheppingen, A. R. V., Starren, A., & Bos, E. L. (2013). The development of a framework to improve health and safety performance measurement: An explorative study. Safety Science, 55, 122–132. https://doi.org/10.1016/j.ssci.2013.01.015
Toplam 57 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Sosyal Güvenlik
Bölüm Makaleler
Yazarlar

Gökhan Tuna 0000-0001-6011-5457

Erken Görünüm Tarihi 10 Haziran 2025
Yayımlanma Tarihi 10 Haziran 2025
Gönderilme Tarihi 23 Nisan 2025
Kabul Tarihi 23 Mayıs 2025
Yayımlandığı Sayı Yıl 2025 Sayı: Özel Sayı

Kaynak Göster

APA Tuna, G. (2025). Predictive Modeling Of Work Accidents Using Lagging Safety Indicators: Perspectives On Social Security Transformation In The 21st Century. Sosyal Güvence(Özel Sayı), 299-346. https://doi.org/10.21441/sosyalguvence.1682358
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