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Informal mentoring, white collar and blue, in a British city.
ABSTRACT
A cross-sectional survey concentrating on informal mentoring
was completed by 404 workers of various occupations in Norwich.
As in previous studies, mentoring was correlated with positive
outcomes for employees. Kram's (1985) factorial model of
mentoring relationships was supported, except in the case of the
blue collar workers; differences inherent in the blue collar
sample, however, provided some evidence in favour of a causal
link between mentoring and the outcomes.
As in other studies, gender differences were insignificant
except in the expected areas of income and, in this study, job
satisfaction.
Levinson's (1978) characterisation of mentors as hierarchical
superiors was supported. A correlation was found between
potential proteges' social orientation at work and the
probability of becoming mentored.
Formal mentoring was not perceived as influential in careers,
although it was considered to be useful for induction purposes.
INTRODUCTION
Mentoring, for the purposes of this study, can be understood
as a relationship - often interactive - between an older, more
experienced person within an organisation and a younger, less
experienced one, serving a variety of developmental functions for
both of them (Kram, 1985). Levinson's model of adult career
development (1978) postulates the likely influence of a mentor
during the stage of early adulthood; one aspect of this
relationship is that it should become more equal as the protege
acquires skills. Adherents of Erikson's epigenetic theory of ego
development (1959) would also expect older successful persons, in
a period of 'generativity', to actively want to be mentors,
passing on the fruits of their experience.
Kram, the leading theorist of mentoring
relationships, postulates two superordinate mentoring dimensions,
career oriented and psychosocial. The career oriented dimension
derives from the functions of sponsorship, coaching, protection,
exposure, and the provision of challenging work for proteges;
they largely relate to experience, rank, and influence.
Psychosocial functions comprise role modeling, counselling,
acceptance, confirmation, and friendship; these are said to
foster "a clear sense of professional identity" as well as aiding
confidence and competence.
"Relationships that provide both kinds of functions
are characterized by greater intimacy and commitment and are
viewed as more indispensable, more critical to development, and
more exclusive than other relationships at work. Relationships
that only provide career functions are characterized by less
intimacy and are valued primarily for the instrumental ends that
they serve in an organizational context. More often than not,
relationships provide a subset of the possible mentoring
functions, and, in general, career functions are more prevalent"
(Kram, 1985).
Other models have been postulated. Schein, for
example, provides a model (1978) concentrating on roles more than
functions; these include the roles of sponsor, role model,
teacher/coach/trainer, leader, protector, opener of doors, and
talent developer. Factor analytic studies by Noe (1988) and
Scandura (1992), however, have broadly supported Kram's model.
Dreher and Ash (1990) found that business
graduates experiencing extensive mentoring relationships reported
receiving more promotions, had higher incomes, and were more
satisfied with their pay and benefits than were those
experiencing less extensive mentoring relationships. No
significant gender relationships were identified, except for the
seemingly inevitable income differential. Other studies have
reached similar conclusions (e.g. Fagenson, 1989).
Dreher and Ash (1990) have noted the problems in trying to
identify causal relationships. 'High-fliers' may be adopted more
readily as proteges; Whiteley et al (1992) discuss social origins
as a possible variable. In other words, mentoring may not be a
cause of success.
Interpersonal attributes are also thought to have a bearing
upon the formation of mentoring relationships. On the side of
the mentor, Levinson (1978) and Clawson (1980) considered a
hierarchical superior to be typical, Whiteley et al (1992)
considered the role of the manager within the organisation,
whilst Olian et al (1988) found that differences in managers'
interpersonal skills significantly affected protege attraction to
the potential mentor, organisational integration of the mentor
only proving significant in the event of weaker interpersonal
skills in the mentor. Considering proteges, Olian et al found
that younger proteges were more likely to be attracted to
potential mentors. Fagenson (1992) found that proteges had
significantly greater needs for power and achievement than
nonproteges.
Another point is that research tends to be American, is
usually based upon studies of managers (often alumni of graduate
business schools), and tends to emphasise formal mentoring (e.g.
Noe, 1988). Although some studies (Berlew and Hall, 1966;
Clawson, 1980) have considered the 'facilitation of
organisational socialisation' - or induction - American mentoring
studies generally relate to major career influences
THE SCOPE OF THIS STUDY
Perhaps it is not entirely coincidental that a British review
of the mentoring literature (Collin, 1979) asked the research
question of whether or not there were typologies of development
for non-managers, and if any mentoring roles existed within the
formal hierarchy. She proposed that the mentor personifies the
company's 'psychostructure' and acts the midwife in the process
of socialisation. One study of MBAs suggested that informal
mentoring was more effective than a formal system, although not
necessarily as fair (Iles and Mabey, 1993).
If we take into account the point that mentoring systems have
been adopted less frequently in Britain than in the U.S.A.
(banking and further education would appear to be exceptions), it
would appear to be unrealistic to make a direct comparison with
American models. Given this inability to test directly whether
or not such systems work similarly across national cultures, the
research may usefully study different phenomena.
It is not suggested, however, that differences ininternational
culture are insignificant (c.f. Hofstede, 1980). Rather that,
contrary to Roche's (1979) U.S. survey of 1,250 executives, where
two thirds had a mentor or sponsor in their early careers, and
Kram's assumption of the development of subordinates as a
mainstream activity within American managerial tasks, the current
British industrial climate is not conducive to the development of
subordinates beyond the parameters of obvious short-term needs.
Formal mentoring systems are rare; their usage will be looked at,
however.
This study concentrates upon informal mentoring, over a
broad(if not thoroughly representative) sample of the working
population within an English city. A factor analysis of the
typology of mentoring relationships will test Kram's (1985) model
in this rather different setting.
The only measure of intrapersonal attributes was the question
about attitudes to work ('social orientation'). This was applied
to Judith Coles' idea of receptivity to mentoring.
HYPOTHESES
1 That mentored individuals should have more job satisfaction,
higher wages and greater career opportunities than non-mentored
individuals.
2 That gender differences will not prove significant (with the
probable exception of income differentials).
3 That the levels of mentoring will vary greatly between
professional and working class careers.
4 That official mentoring will not appear to be widespread, and
that it will not be viewed as particularly beneficial by its
recipients.
Further questions to be asked:
Are Kram's factor analytical qualities valid in Britain?
Will the mentor typically be a hierarchical superior?
RESEARCH DESIGN AND METHODOLOGY
The questionnaire
A correlational cross-sectional survey (see Appendix A), this
distinguished the following demographic groups: gender,
occupation, age, and income. Three attitudinal scales (questions
2.1 - 2.3) were cruded tests of job satisfaction, subjective
attainment (c.f. Lawrence, 1984, on the 'social clock'), and
social orientation at work. The latter, as well as measuring
affiliation needs, also served as an indirect indicator of
receptivity to mentoring.
Those who considered themselves to have been greatly
influenced in their careers were asked to continue with some
details of the mentoring relationship and then a global measure
of mentoring practices. Questions represented different factors
postulated by Kram (1985); see Appendix B. The measure was drawn
from Dreher and Ash (1990), who themselves selected items used by
Noe (1988) and Whiteley et al. (1988). Minor amendments were
made to assist comprehension by a wider range of respondents than
in the previous studies. The researcher added a 19th. question,
from the Noe study, in order to include an essential part of
coaching.
Brief questions on formal mentoring were asked of all
respondents, with room for comments. It seemed likely that
formal mentoring would be scarce in the British context, so
little space was devoted to this issue. The issue was placed at
the rear of the questionnaire to avoid influencing choices made
about informal influences.
The sample
Questionnaires were distributed via simple random sampling of
the working population of Norwich. The guiding priorities were
to gain information speedily and over a broad range of
occupations and incomes. Accessibility of subjects within the
time and personal budget available meant that a truly
representative range was out of the question. Random sampling
was therefore simple rather than proportional, although still
intending to be numerically representative.
The Census of 1991 considered the population of Norwich, aged
between 16 and 65, to be 76,864. The working population of
Norwich will be less when unemployment is taken into account, but
with the well-known phenomenon of commuting - into Norfolk's only
city - the working population probably ranges between one and two
hundred thousand people. Krejcie and Morgan (1970) recommend a
sample size of 384 for a population of between 75,000 and a
million; Roscoe (1975) recommends a maximum of 500 for such
studies.
One city was chosen to avoid the confounding variable of
economic fluctuations across geographic areas. Certain points
should be noted about the context, however. The city of Norwich
is primarily populated by caucasian people; indeed, it has the
dubious distinction of being called the 'last white city' by some
neo-fascists. Racial factors such as those considered by Thomas
(1990) therefore could not be covered; arguably, this excludes
another potentially confounding variable.
A distinction of the county of Norfolk is that its relatively
slow pace of life is popular and the area is therefore often
known as the 'graveyard of ambition'. The implications of this
for such factors as mobility and promotion should be considered
when considering the generalisability of this study to other
parts of Britain.
Data collection
901 questionnaires were distributed, 438 (48.61%) returning,
of which 3 were discarded as unusable. 404 arrived on time for
analysis. Questionnaires were distributed personally by the
researcher in the case of individuals and very small groups,
otherwise via managers and other officials. With the exception
of a few organisations which made alternative arrangements, all
individuals received a questionnaire with (attached by paper
clip), an envelope, stamped first class and printed with the
researcher's Norwich address. Where requested, the researcher
would summarise verbally the contents of the questionnaire; in
larger organisations, the researcher requested distribution to a
range of hierarchical levels. Follow-up calls were only made at
the suggestion of questionnaire recipients (a rare occurrence).
Questionnaires went out in the following proportions,
essentially based upon accessibility:
banks 20%; post office 12%; social workers 12%; fire service 11%;
diverse civil servants 10%; hospital staff 6%; police 6%;
education 4% estate agents 2%; recruitment agencies 2%;
voluntary\charitable organisations 2%; railway employees 1%;
others, including self-employed people, taxi drivers, sales and
bar staff, various professionals, and retired individuals 12%.
Of the 404 questionnaires analysed, the approximate
proportions were:
banks 26.5%; hospital\education\social work 14.5%; post office
9.5%; police 8.5%; civil servants 8.5%; fire 5% rail 2%;
miscellaneous 25.5%.
Particularly for the purposes of factor analysis, the
occupational groups were conflated into blue collar (125) and
white collar (279) workers.
Piloting
Six pilot questionnaires were distributed to friends from a
variety of work backgrounds. Various criticisms of format led to
minor changes in the questionnaire, including the inclusion of
HND as an academic qualification level. The relevance of the
subject matter to particular workers was questioned.
Of particular interest was the idea of 'receptivity to
mentoring' as a likely influence on the take-up of mentoring.
Judith Coles, one of the pilot respondents, raised this as an
issue; as discussed, other researchers have looked at rather
specific attributes influencing the mentoring process. The
researcher decided to use the question about social orientation
at work as an indirect measure of this; those who saw work as
divorced from social aspects were likely to be the people who,
according to Coles, tended to pass over potential mentors.
Lack of time prevented a thorough pilot distribution of
questionnaires. An analysis of the first 50 mentoring scales for
those with mentoring relationships, indicated strong internal
consistency; a subsequent Cronbach Alpha reliability test on the
total 177 cases factor analysed gave a coefficient of .8967 on
the first 18 items of the mentoring factor scales, .9027 with the
19th. question added.
Consistency of the questions on formal mentoring was highly
unsatisfactory (.1595). The attitudinal measures were poor
(.5963), although the removal of the social orientation scale
from the calculations gave the fair result of .6350.
Analysis methods
Factor analysis was used on the mentoring behaviour scales,
studying all of those with mentors and also groups divided into
blue and white collar occupations and also by gender. The direct
method of analysis was Principal Components, with an oblique
rotation technique (Oblimin). Kaiser's criterion (Eigenvalue >
1) was chosen for deciding upon the number of factors to be
extracted, supported by the scree test (Cattell, 1978). For
clarity, it was decided to limit analysis of coefficients to a
minimum of .5. Structure matrices were usually chosen for
analysis (a pattern matrice was used in the female category
because it resembled the number of factors in the original
statistics); these appear in Appendix H.
Non-parametric methods were generally chosen for tests
involving Likert scales. Although not based on interval data, it
was felt reasonable to apply parametric testing to income given a
relatively normal distribution.
Similar considerations allowed the use of parametric testing
on the aggregated scores of the mentor behaviour scales, which
served as a measure of the quality of mentoring. This dependent
variable will be referred to subsequently as 'addfacts'.
Additional mentoring independent variables were the existence
of mentoring or otherwise, the number of mentors, and the
duration of the most important of these relationships.
RESULTS
1 That mentored individuals should have more job satisfaction,
higher wages and greater career opportunities than non-mentored
individuals.
This was supported overwhelmingly; those individuals who had
been mentored differed from those who had not in terms of income
(Kruskal-Wallis p. <.0001), job satisfaction (p <.0002) and
subjective estimates of career level achievement (p <.0002).
It should be noted, however, that the same statistical test
uncovered similar relationships between academic qualifications
and the dependent variables (income p <.0001; job satisfaction p
<.005). Although this test failed to find a significant
relationship with career level (chi square 8.4451 p <.1333), the
Sign test did (p <.05 2-tailed). Unsurprisingly, qualifications
and mentoring correlated (Spearman r= .0946; p <.05 1-tailed).
Levels of perceived attainment varied interestingly, however,
when distribution was examined in the light of qualifications. O
level standard respondents appear to have fared the worst
(Appendix E). Those with no qualifications (Appendix F),
although clearly having the expected large proportion who have
failed to achieve, have a higher mean than those with 'A' levels
or higher (Appendix G) and have outstripped them in terms of
'over-achieving'.
The quality of mentoring, as measured by the summation of
factorial item scores ('addfact'), did not correlate
significantly with income (Pearson), but was related to job
satisfaction (Spearman .2491, p <.001) and to subjective
attainment (Spearman .2009, p <.01). The number of mentors
produced a similar set of relationships (Spearman: n.s.; r=.2491,
p <.001; r=.2009, p <.001).
2 That gender differences will not prove significant (with the
probable exception of income differentials).
As Appendix D shows, males and females responded in almost
equal numbers. As expected, there was a significant gender
difference in income (independent t-test p <.001). Gender also
correlated with job satisfaction (Mann-Whitney p <.001); the
expected levels measure was not significant.
The hypothesis as a whole is supported by the available
evidence. Male and female respondents did not differ
significantly in terms of 'addfact' (independent t-test), number
of mentors (Mann-Whitney) or in the proportion of those mentored
(Mann-Whitney; statistics in Appendix D).
The relationship between gender and affiliation, as
represented by the social orientation measure, was not
significant (Mann-Whitney). The results were supported by
separate analyses of mentored and non-mentored individuals.
3 That the levels of mentoring will vary greatly between
professional and working class careers.
The null hypothesis may not be rejected here. Of the 404
respondents, 125 were blue collar workers, 279 white collar. Of
the 179 respondents (44.31%) who claimed to have had significant
personal influences in their lives, 56 were blue collar (44.8%)
and 123 were white collar (44.09%).
The differences between the occupation categories on quality
of mentoring (addfactors) and duration of the most important
relationship were insignificant (Mann-Whitney). Blue collar
workers claimed to have had more mentors (Mann-Whitney, p <.001).
Interestingly, whilst white collar workers were generally
better qualified academically (Mann-Whitney p <.0001), blue
collar workers were better paid (Kolmogorov-Smirnov p <.02 2-
tailed). Differences pertaining to job satisfaction and
subjective expectations proved insignificant.
Of particular interest for its implications for hypothesis 1
is that blue collar workers with no academic qualifications, who
had also reached above their expected level of attainment,
claimed to have had significant personal career influences
(Spearman, p <.02 2-tailed).
4 That official mentoring will not appear to be widespread, and
that it will not be viewed as particularly beneficial by its
recipients.
Of the 404 cases, 61 (15.09%) had had formal 'mentors';
another 61 had had 'buddies' or some other such allocated
assistance. Correlations between these categories and perceived
usefulness were not significant; respondents' opinions appear to
have been supported by insignificant correlations with income,
job satisfaction and career level assessments (Spearman).
A negative correlation with the existence of informal mentors
occurred in both cases (r = -.1249 p <.02, r = -.0984 p <.05;
Spearman 2-tailed). Comments from those who had found these
formal roles useful generally revealed that they were essentially
induction procedures, run for a few weeks or months, rather than
ongoing career assistance. This seemed particularly widespread
in the blue collar occupations, and rather reflects the view of
the British commentator, Audrey Collin, that the mentor is an
agent of socialisation.
Are Kram's higher order factors valid in Britain?
The factor analyses conducted in this study tend to support
Kram's general grouping of factors into psychosocial and career
oriented higher order factors. The initial statistics for the
factorised group as a whole were as follows:
Eigenvalues % of variance cumulative %
VC1 7.14827 37.6 37.6
VC10 2.14487 11.3 48.9
VC11 1.32133 7 55.9
VC12 1.05072 5.5 61.4
After rotation, the first factor contained 5 psychosocial
elements (mainly 'counselling') and 2 apparently career-oriented
elements. The latter, however, comprise sharing of the mentor's
history with the protege (question 14) and similar attitudes and
values (18); these particular elements, chosen by Noe (1988) to
represent the coaching and role model factors could quite easily
be interpreted as being fundamentally psychosocial in function.
The second factor comprises 4 career oriented elements (3
exposure/visibility and 1 challenging assignments).
Factor three comprises 6 career-oriented elements and 2
psychosocial elements. Again, classification seems to be the
source of the apparent discontinuity: the 'counselling' role
involves discussions of competence and promotion (question 13),
with 'acceptance/confirmation' being encouragement to behave in
new ways on the job' (16). Interpreting these as career
oriented rather than psychosocial does not seem to be
constraining facts in favour of theory unduly.
The fourth factor comprises three career functions.
Factors correlation matrix:
Factor 1 Factor 2 Factor 3 Factor 4
Factor 1 1.00000
Factor 2 .23823 1.00000
Factor 3 -.47601 -.28740 1.00000
Factor 4 .28727 .32986 -.24768 1.00000
The strong negative correlation between factor 1 -
psychosocial - and factor 3, a strongly career-oriented factor,
are also very suggestive of Kram's higher order division.
When the white collar occupational segment was studied
independently, Kram's higher order functions were supported with
even greater clarity.
Eigenvalues % of variance cumulative %
VC1 6.30568 33.2 33.2
VC10 2.31200 12.2 45.4
VC11 1.35617 7.1 52.5
VC12 1.19400 6.3 58.8
VC13 1.01946 5.4 64.1
Factor 1 comprised 4 psychosocial elements, with question 14
again; another apparently career-oriented element is question 18,
pertaining to similar attitudes and values. The 5 elements in
Factor 2 seem to cover coaching and advancement; the inclusion of
questions 13 and 16 again do not seem to contradict this. Factor
3 is career oriented, comprising exposure and visibility (3
elements) and challenging assignments (1). Factor four
comprises two role model elements, the fifth factor two
protection elements.
The Blue Collar category, however, shows a remarkably
different topology. The initial statistics are as follows:
Question Eigenvalue % of variance cumulative %
VC3 7.14418 55 55
VC6 1.12195 8.6 63.6
Correlation -.56988
Both factors, as shown in Appendix H, contain a mixture of
psychosocial and career-oriented elements (in Kram's
formulation); the breadth of the mixture does not suggest
blurring of interpretive classification. The nine elements of
Factor 2 all feature amongst the thirteen in Factor 3; all are
negative correlations, presumably indicating bi-polar
relationships.
Although gender divisions show fewer changes from the topology
of the whole sample, differences do exist: Initial statistics
follow for the men.
Question Eigenvalue % of variance cumulative %
1 7.43755 39.1 39.1
10 2.20094 11.6 50.7
11 1.35305 7.1 57.9
12 1.07563 5.7 63.5
13 1.01525 5.3 68.9
Factor one has 2 unambiguous career-oriented elements, role
model (question 17, example of how things should be done) and
sponsorship (7, promotion of career interests). Factor two is
exactly the same as that for the whole factorised sample. Factor
three is very similar (minus question 8; plus 10 and 7). Factor
four retains the 'protection' elements, 7 having been subsumed
into the previous factor. Factor 5 contains two career-oriented
elements (6 and 8). As in the main matrix, there is a large
negative correlation between factors one and three.
Factor correlation matrix:
Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
Factor 1 1.00000
Factor 2 .21636 1.00000
Factor 3 -.49934 -.21376 1.00000
Factor 4 .21271 .18390 -.16940 1.00000
Factor 5 .23983 .01944 -.21288 .05559 1.00000
106 of the 123 blue collar workers (86%) were men. Although
causation is unclear, the relationship between worktype and
gender (Chi-square .45894, p >.00001) suggests that the nature of
the blue collar jobs may be an influential variable in explaining
the difference in factor 1, given the great disparity of this
category from all other factor analyses, the even gender spread
in the study as a whole and the solid adherence of the white
collar sample to the sample norm. A discussion of the
qualitative responses to formal mentoring (hypothesis 4) is
supportive of this argument.
Initial statistics for the female category are as follows:
Question Eigenvalue % of variance cumulative %
1 7.04670 37.1 37.1
10 2.33318 12.3 49.4
11 1.39170 7.3 56.7
12 1.26948 6.7 63.4
13 1.06172 5.6 69
Factor correlation matrix:
Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
Factor 1 1.00000
Factor 2 .23175 1.00000
Factor 3 .09018 .03620 1.00000
Factor 4 -.42860 -.34951 -.10744 1.00000
Factor 5 -.07441 -.01403 -.04889 .05991 1.00000
The first two factors, responsible for half the variance
covered by the large Eigenvalues, are similar to the overall
mentored sample. Differences occur in the lower factors
(Appendix H holds the details).
Will the mentor typically be a hierarchical superior?
This was generally the case:
line managers / supervisors 49.2%
more senior managers 20.3%
older / more experienced colleagues 15.8%
colleagues generally 5.6%
very senior managers (e.g. directors) 2.8%
others (e.g. consultants, wives) 6.2%
As the line chart in Appendix C indicates, it is generally
within the line manager's ability to provide the best quality
mentoring (by the addfacts measure).
Additional results
The social orientation measure correlates with the existence
or otherwise of a mentoring relationship, as predicted by Coles'
theory of receptivity to mentoring (Mann-Whitney p <.001).
DISCUSSION
The support for the first hypothesis, that mentoring is
related to outcomes, reflects much of the literature referred to
earlier. This result appears to have generalised from American
studies of formal mentoring to a primarily informal system -
perhaps this is rather an oxymoron - in Britain. It is not
surprising that factor analysis reveals a closer adherence by
white collar occupations to Kram's (1985) dichotomy of career
orientated and psychosocial factors; this classification has more
in common with the American respondents.
Although the blue collar category was originally included to
examine class differences (which appeared insubstantial in the
light of hypothesis 3), the results pertaining to it may well
have a bearing on a regular problem of cross-sectional studies:
the direction of causation. This perennial is of course
suggested by the correlation between qualifications and outcomes;
have qualifications or accompanying impressions of being a 'high-
fliers' attracted mentors. Whilst this may be a confounding
variable in the white-collar occupations, this appears to be less
likely in the blue-collar category, where a less academically
qualified contingent seems not to differ significantly in
mentoring levels. The correlation between expected levels of
attainment and claims of significant personal career influences,
when pertaining to those without any academic qualifications,
does rather suggest that 'who you know matters more than what you
know' at certain stages of some careers.
Unfortunately, no such additional evidence allows such
commentary to be applied to the relationship between mentoring
quality (as measured by 'addfacts') and subjective measures.
Results relating to gender differences appear to reflect the
American studies. No differences in mentoring outcomes occurred;
the usual income differential, however, was also accompanied by
one relating to job satisfaction. No great differences in
mentoring experiences emerged from the factor analysis.
Differences in the male responses to factor analysis probably
reflect the situation in blue-collar occupations. A difference
occurs in the topology of the mentoring, although not in non-
factorial measures. Kram's factors do not appear to cross the
class barrier. The resultant 'feel' of the analysis (c.f. Child,
1990, on the reliance on subjective judgement relative to other
statistical methods) is one of a very personal attention to a
protege's advancement; perhaps division between advancement and
interpersonal issues is more characteristic of white collar work
places.
This may be interpreted as supporting Kram's assertion (1985)
that relationships providing both both kinds of functions are
particularly beneficial for development. The complete blurring
of definitions in the blue collar classification means, however,
that the model has no construct validity in this domain and
should not, therefore, be used for extrapolations here.
Kram's model is supported generally, however; its extension
beyond both country of origin and the usual respondent population
is impressive. The strong negative correlations between strong
psychosocial and career-oriented factor clusters are particularly
indicative of her superordinate factors. Her claim (1985) that
career functions are generally more prevalent may be domain
specific, however, given the formal systems in the U.S. In this
study, Factor 1, with the largest share of the variance by far,
has a predominance of psychosocial loadings.
British employment - if the Norwich survey is representative
- does not appear to support formal mentoring in terms of
influencing careers beyond organisational socialisation (which
would appear to be primarily task-related). Given the research
on efficacy of formal and informal systems (Iles and Mabey,
1993), this may not be problematic. Many of the recipients of
formal mentoring did seem to appreciate its value as a tool of
induction. It just does not comprise the general career
influence portrayed by Kram and supports the assertion that
British employers are only likely to organise systems for meeting
short-term needs.
Whilst Iles and Mabey cast doubts upon the fairness of
informal allocation, this study would suggest that the likelihood
of becoming mentored lies somewhat in the personality, or
possibly conception of work, of the would-be protege. A measure
of social orientation that was designed to look at gender
differences in affiliation needs (not significant) was also used
as an indirect measure of receptivity to mentoring. This is
supportive of Judith Coles' observations: her own mentor,
although invaluable to her, was not 'discovered' by several of
her colleagues; when she herself became a mentor, some used her
experience, others 'did not want to know'.
In terms of mentor characteristics, the pre-eminence of
hierarchical superiority is in line with Levinson's (1978)
conception of the mentoring role.
SOME CRITICISMS OF THE CURRENT STUDY
Textual problems
One of the flaws in the questionnaire itself was the original,
ambiguous, classification of the global mentoring scales
questions by Noe (1988). As noted earlier, the respondents'
answers generally clustered meaningfully; Noe's categorisations
sometimes lacked validity, failing to measure that which they
purported to measure.
In making alternative interpretations, the researcher may be
accused of, at worst, constraining the facts to fit the theory,
or - still problematic - making comparison with previous results
rather difficult. Future replication is not a problem, however,
given the explanation in the text of which elements were re-
interpreted.
The researcher's own questions left something to be desired.
These were of low reliability. A proper pilot study was not
conducted (a result of temporal and fiscal pressures). The job
satisfaction measure was so crude as to be unworthy of debate
relating to theory. The only excuse that may be offered is that
the need to study the other focal points without producing an
unwieldy questionnaire rather encouraged this dabbling.
The use of an affiliative measure - and a riskily colloquial
one at that - to indirectly measure receptivity to mentoring was
of dubious validity. It really covered attitudes to work. It was
shown to lack consistency and further study would be needed to
see what is the underlying factor correlating with take-up of
mentors.
Some textual errors succeeded in surviving the small pilot
scheme. At one point, the text refers to influences on careers;
more than one respondent pointed out that some influences are
malevolent, the very opposite of the benevolent mentoring under
examination. A worse error was the 'definitely ot at all' at the
crucial stage of the study where the respondent decided on
whether or not he or she had been mentored. Fortunately, most
respondents underwent the same Gestalt interpretation as the
pilot proofreaders (perhaps being used to Likert scales); most of
those who did follow the instruction literally gave subsequent
answers which explained where they stood, but this error was
certainly unhelpful and led to discards of questionnaires.
Certain areas of study were discontinued. Data to be used to
examine changes in mentoring over time and age-related qualities
of mentoring relationships were rendered inaccessible by the
database files becoming corrupt; the researcher had made the
mistake of loading a software update immediately it arrived,
rather than trying it out on a fresh piece of work.
This technical problem also led to an inability to count
elements arising from qualitative responses (e.g. how many formal
mentors were seen as useful in the realm of induction).
Analysis problems
Strictly speaking, significance levels should have been
determined before statistical tests were conducted, rather than
using the readout from a computer program.
Given more time, the researcher would have consulted about the
usage, interpretation and presentation of factor analysis
results. No explanation was given for the choice of an oblique
rather than an orthogonal rotation technique. Similarly, no
sensible rationale lay behind the choice of structure over
pattern matrices.
Worse was the switch to a pattern matrice when analysing the
female sample, making comparisons with other topologies a rather
dubious undertaking. The idea of doing this for closer adherence
to the original statistics defeats the object of the rotation, to
give derived solutions.
Sampling
The smallness of the mentored sample of 'blue collar' workers,
coupled with the reliance on post office workers, firefighters,
and police officers, may have biased the results in favour of
workers in large (and generally uniformed) organisations. More
generally, the overall sample may well have been representative
of the city's working population, but the convenience sampling
did not give random access to different levels of employee
status.
As noted earlier in the study, Norwich was not an ideal
population for hoping to extrapolate to other areas of the
country, let alone elsewhere.
Whilst the method of data collection coincided with a good
response rate for questionnaires without follow-up (Bailey,
1978), the use of both personal distribution and first class mail
for completed questionnaires makes it hard to ascertain which was
the effective variable. Also, the distribution process could
only be replicated fully by the researcher.
CONCLUSION
Mentoring is related to outcomes; this result appears to have
generalised from American studies primarily of formal mentoring
to informal mentoring in Britain. Similarly, Kram's (1985) model
of the nature of mentoring relationships is supported.
The domain into which her model does not generalise - the blue
collar occupational category - provides useful evidence about the
more general outcomes. The blue collar sample did not differ
significantly in general outcomes, only in factorial responses
about the mentoring process, where the distinction between
career-oriented and psychosocial factors seemed non-existent.
Similar correlations existing between mentoring and outcome
measures, without the confounding variable of academic
qualifications, are supportive of a theory of causal direction in
which mentoring influences progress (as opposed to being a
product of other forces, merely accelerating an existing
momentum).
Gender findings replicate those of other studies. Differences
are insignificant, except in the expected areas of income and, in
this study, job satisfaction. Male differences were probably
attributable to phenomena within the blue collar sample, where
men predominated.
In terms of mentor characteristics, the pre-eminence of
hierarchical superiority is in line with Levinson's (1978)
conception of the mentoring role.
Formal mentoring appears well suited to induction, its current
usage in Britain. This study suggests a relationship between the
up-take of informal mentoring, with its broader implications, and
the receptivity of the potential protege; social orientation at
work was the measure used.
Recommendations
Whilst respondents tended to be scathing about the notion of
formal mentors as serious influences on their careers, they did
seem to appreciate their value in learning the ropes. As this
system works, it shouldn't be changed.
Given the apparent efficacy of informal mentoring, however,
encouragement of this would probably be of value to employees
(and arguably other parties). If formal methods are introduced,
then mutual choice of persons in the relationship may eradicate
some of the negativity of responses to current formal systems.
Perhaps more realistic would be an ethos of mentoring; London and
Stumpf (1986), for example, recommend that people aged 55-75 -
'young elders' - should be viewed as valuable resources, who may
be encouraged to become mentors, also providing expertise in
those areas in which they are not rendered technologically
obsolete.
The point about receptivity to mentoring suggests, however,
that a more general education about the nature of work (here, the
possible extrinsic benefits of social interaction) would be
valuable. Perhaps such an intervention would best be made at a
level of pre-vocational careers work. An accompanying ethos
would need to be in existence at workplaces, however, if
disillusionment is not to be the primary outcome.
Such practical suggestions assume that the current research
undertaken is reliable, with a broad base of external validity.
Areas of further research could include similar research in other
areas of the country and elsewhere, preferably with a larger and
more representative survey of blue collar workers. It would be
particularly desirable to know whether or not the one
generalisation failure in Kram's model of mentoring processes is
embedded in the British (or even Norwich) context. Analysis
could also examine alternative existing models of mentoring (e.g.
Schein, 1978) applied to this occupational category; new factors
may have to be sought, however.
Also, research should address the question of whether or not
social orientation is the key to receptivity to mentoring. An
alternative to, for example, factor analysis, may be to devote
the bulk of a questionnaire to a variety of attributes and work
attitudes which may correlate with mentor take-up.
ACKNOWLEDGEMENTS
Clearly, the work could not have been undertaken without the
participation of a large number of people totally unknown to me
personally, workers in Norwich of various kinds. During a time
when my confidence was low, I was particularly heartened by the
interest, assistance and encouragement of Bill Edmonds, Training
Officer with Norwich City Council.
As my references to her in the text suggest, I was
particularly helped by the ideas of Judith Coles, Proprietor of
DeskToPs, Prince of Wales Road, Norwich.
My tutor, Dr. Jenny Kidd, put up with the vagary of trying to
timetable the equivalent of almost 18 months research into about 6
weeks.
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