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Arunav Kaul
Subordinate courts are courts of first instance, forming the bedrock of the judicial system in India. They are burdened with close to 2.5 crore pending cases. In 2016-2017, as many as 2 crore cases were filed across the subordinate courts in the country. It is therefore important to delve into the issue of judicial strength in the backdrop of the increasing case load.
There are four important questions that surround the issue of judicial workforce in subordinate courts, which this article seeks to address:
What is the variation in judicial strength in subordinate courts?
One can clearly note in Figure 1 that Maharashtra, which has the second highest number of cases filed as well pending in the country, functions with an average of 2,168 judges, the highest in the country. However, Uttar Pradesh (UP), which has nearly twice the number of pending cases and filings when compared to Maharashtra, functions with an average of 1,792 subordinate court judges.
Although the sanctioned strength of judges in UP has been more than that of Maharashtra’s, in the past two years, UP’s working strength of judges has been much lower when compared to Maharashtra. A similar pattern can be seen in Madhya Pradesh (MP) and Kerala. While both states have equal number of cases filed and pending, MP functions with an average of 1,279 judges, whereas Kerala enjoys only 415 subordinate court judges.
What is the basis for this variation?
Should pendency of cases or volume of cases filed in courts determine the number of judges required? As per Figure 1, this does not seem to be the case, at least for the last two years. Is there any other factor that determines such variance? Honestly, there does not seem to be a definite answer to this. However, there maybe two primary reasons attributed to this.
Firstly, the rate of disposal per judge method may be one of the factors causing the variance, although it is not a conclusive answer. The method was first proposed in the 245th Law Commission’s Report in 2014 to calculate judges’ strength in subordinate courts, to tackle the backlog of cases in courts. As per this method, courts that have a lower rate of disposal will be allotted more judges as compared to courts that have a higher rate of disposal.
This can be seen in Figure 2, which demonstrates the trend in the average disposal per judge for the past two years in the subordinate courts.
Although as per Figure 2, the trend in terms of rate of disposal per judge and judges’ strength does not seem to be uniform across all the courts, it does throw a certain amount of light in explaining the variation in a few states. For instance, UP, which has the highest number of cases filed and pending in the country as shown in Figure 1, has lower judges’ strength when compared to Maharashtra.
One of the reasons for such variance may be attributed to the rate of disposal per judge, as UP seems to have a much higher disposal rate per judge when compared to Maharashtra. Similarly, Kerala and Rajasthan that have similar number of pending cases have much varying judicial strength. This may possibly be due to the fact that Kerala has a much better rate of disposal per judge when compared to Rajasthan.
Secondly, increasing vacancies may be another reason for such variation. Over the last two years vacancies in subordinate courts have increased from 23 per cent to 25 per cent. Since various states face irregular increase and decrease of judges in different quarters, this may be contributing to the unmethodical variation of judges in states.
What are the different methods that have been used to calculate judicial strength in the past?
The infographic below presents a time-line of different methods proposed to calculate judges’ strength in the subordinate courts. The infographic maps different methods starting with the judge to population ratio method proposed in 1987, up till the unit system-based method proposed in 2017.
One of the main criticisms of the rate of disposal method proposed by Law Commission was that it did not differentiate between different types of cases, be it a serious murder case or a petty offence, therefore, adopting an incorrect approach.
Hence, there was a need to come up with a weighted case load model that can differentiate between different types of cases and accordingly calculate judicial strength. The National Court Management Systems Committee (NCMSC) proposed a unit system-based interim model to calculate judicial strength for subordinate courts, which remains to be the status quo till date.
The unit system essentially is a performance assessment criterion to evaluate judges based on the cases disposed. Depending upon the severity of the case, each type of case is given certain number of units, which varies from one state to another. Judges in subordinate courts are assessed based on the points achieved in every quarter. Based on this criterion, the NCMSC proposed a unit system-based model as an alternative to the Law Commission’s rate of disposal method.
In 2017, the Supreme Court rejected the Law Commission’s report. The final model to calculate judges’ strength, which was to be created by December 31, 2017, is yet to be seen.
What is the best method to calculate judges’ strength?
The answer to this question is “none of the above.” Both, the judge to population ratio, and the rate of disposal method, suffer from serious flaws. While the latter does not take into account the workload of courts since the focus is on population, rather than filings or number of cases pending, the former does not differentiate between different types of cases as explained above. The unit system-based method proposed by the NCMSC is also inadequate, as there is no scientific rationale on which units are decided for each of the category of cases in different states.
The best alternative would be a time based weighted case load model which proves to be the most scientific method to determine judicial strength. The model is widely practiced in the United States. It takes into consideration three important indicators i.e. the time spent by judges on different types of cases, average annual filings or number of pending cases and total time available per judge in a year.
The resulting value would indicate the number of judges that will be required to handle the current caseload of a particular court. With the availability of yearly court-related statistics, the introduction of the National Judicial Data Grid, and the e-courts system (a government website that provides real-time information of progress of cases registered in courts), carrying out such a study has become a reality.
It is therefore important that courts adopt a scientific model that can accurately calculate adequate judicial strength. Conducting a ground level study will help in understanding the varying workload of different courts which can be used to compute the workforce. While the final model is yet to be finalized, let us hope that India marches towards scientific reforms for assessing judicial strength in subordinate courts.
Arunav Kaul is a research associate at DAKSH, Bengaluru, a civil society organisation that undertakes research activities to promote accountability and better governance in India. The views expressed here are personal.