INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue XI November 2025
In Table 6, a multiple regression analysis was conducted to examine whether current (Now) culture, preferred
culture, organizational commitment, and school climate predict teacher absenteeism. The overall model was not
statistically significant, R = .016, R² = .004, F(4, 315) = 1.305, p = .268, indicating that the set of organizational
variables explained approximately 0.4% of the variance in absenteeism.
At the predictor level, none of the coefficients reached conventional significance (α = .05). Now Culture
demonstrated a negligible effect on absenteeism, B = 0.199, SE = 2.693, β = .004, t(315) = 0.074, p = .941, with
a wide 95% CI for B [−5.11, 5.50], suggesting substantial uncertainty around the estimate. Preferred Culture
showed a small, positive, and nonsignificant association, B = 1.855, SE = 1.703, β = .061, t(315) = 1.089, p =
.277, 95% CI [−1.50, 5.21]. Organizational Commitment likewise yielded a small, nonsignificant effect, B =
0.245, SE = 0.212, β = .098, t(315) = 1.157, p = .248, 95% CI [−0.173, 0.663]. School Climate showed the largest
standardized effect in magnitude and approached significance, B = −0.411, SE = 0.210, β = −.166, t(315) =
−1.962, p = .051, with a 95% CI [−0.825, 0.003], narrowly spanning zero. Although this trend suggests that more
positive climates may be associated with lower absenteeism, the effect did not meet the threshold for statistical
significance and should be interpreted cautiously.
Interpretively, these findings indicate that, in this sample, absenteeism appears weakly related to the measured
organizational factors when considered simultaneously. The very small model R² and the non-significant
coefficients align with the possibility that personal, health-related, and systemic influences (e.g., illness, family
responsibilities, commute constraints, administrative workload, policy shifts) exert stronger effects on
attendance patterns than organizational culture, commitment, or climate alone. Moreover, the borderline result
for School Climate suggests that, while organizational conditions may matter, their influence could be indirect,
moderated (e.g., by workload or leadership support), or masked by unmeasured variables. Future analyses that
incorporate objective attendance records, broader covariates (e.g., health, caregiving burden, travel time), and
multilevel designs (e.g., teachers nested within schools) may yield a more nuanced account of absenteeism.
Longitudinal models could also clarify temporal precedence—whether changes in climate or commitment
precede changes in attendance.
Practical implications for school leaders include: (a) continuing to strengthen climate through supportive
leadership, professional collaboration, and buffering from external pressures, given its near-significant and
theoretically plausible negative association with absenteeism; (b) pairing organizational initiatives with targeted
personal supports (e.g., wellness programs, flexible scheduling, streamlined administrative tasks); and (c)
monitoring attendance using non-punitive, developmental approaches that emphasize early identification and
assistance for at-risk staff. Collectively, such strategies address both organizational context and the
personal/systemic drivers likely to shape attendance behavior.
Prior studies have emphasized that a strong and cohesive culture can reduce absenteeism by fostering shared
values and behavioral norms (Lok & Crawford, 2004). However, the non-significant effects of both Now Culture
and Preferred Culture suggest that cultural perceptions may not directly influence absenteeism unless they are
deeply internalized or aligned with personal values (Gregory et al., 2009).
Meyer and Allen’s (1991) three-component model posits that affective commitment is most predictive of
attendance. The lack of significance here may indicate that employees’ commitment levels are either low or
overshadowed by external factors such as personal health, family responsibilities, or job stress (Johns, 2008).
Although climate showed the strongest effect among the predictors (β = −.166), it narrowly missed statistical
significance. This aligns with Schneider et al. (2013), who found that a positive climate can reduce withdrawal
behaviors, but its impact may be moderated by other variables, such as leadership support or workload.
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