head teacher's data (gender, qualifiwation, teaching expierience, administrative experience, and whether received training as a head teacher.) 17. The complete list of variables on which information was collected can be found in Annex A. The differences between the schooltypes can be easily judged, variable by variable, from Tables 2-4, which reports means and standard deviations (in pdrentheses) for variables Included in this study.<sup>6</sup>

## _Pupil Level Differences_

18. As cali be seen in Table 2, the highest average scores in both subjects are obtained at the highfee-paying and former Group A schools. As already pointed out under the description of varia3les, scores range from 1 (low) to 9 (high); scores of 4-9 are considered passing. Table 2 also illustrates the differences in intake of the different schooltypes by stuJent background variables, which may account for some of these differences in achievement. Relative to an average of 44% of the fathets of the sampled student population having no education, 66% of the fathers of district council school pLpils were uneducated, against lows of 7% and 14%, respectively, for former Group _A_ and high-fee-paying schools. Whereas more than half of the fathers of the pupils sampled in the high-fee-paying and Group A schools had secondary education, only 1 to 2 % were similarly educated at the district council, Group B, and lowfee-paying schools. In addition to coming from less educated families, students attending the low-f3epaying and district council schools come from larger families and district council school pupils take longer, on average, to complete primary education.

# **_Class_** _Level Differences_

19. Information collected at the class level illustrates significant schooltype differences as A -Il (Table 3). The lowest percentage of female teachers are found in district ~.ouncil schools, 8% on average, whereas 79% of the teachers in the high-fee-paying schools surveyed were women.<sup>7</sup> 77% of the teachers surveyed claimed that they had ieceived 'standard' teacher ,raining requiring completion of Form IV plus

- 6 Only those variables capable of being utilized in the study are reported in Table 2. This is not the complete list, because in the data entry, the value 0 used for 'non-response' overlapped with a real value of 0, mak-ing these variables unusable. The variables which had to be eliminated from the analysis for this reason included: PRESCHYR (Years spent in pre-school); DAYSABS (Number of days a pupil was absent from school in terms I and 2 of 1990); EHWTIME and MHWTIME (hours per week devoted to English or mathematics homework, respectively); TCHABS (Number of days a teacher was absent from school in terms 1 and 2 of 1990); EUNSUP and MUNSUP (Unsupervised English/mathemnatics study hours per week); and LIBBOOKS (Total number of books in the school library).

- 7 On its own, one cannot mqke much of such a statistic, but further investigation would be appropriate to determine the reasons behind such gender disparities in teacher allocation. It could reflect the inadequacy of teachers' housing and the difficulty of young, unmarried women moving out to rural areas different from their own, particularly as untrained or less experienced, new recruits comprise the majori:, f those taking up such positions.

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