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For faculty with a teaching preference, however, results are considerably different, particularly by gender. Yet, advisor sponsorship has no effect for male faculty with a teaching preference.
However, it has no effect on placement in the highly prestigious teaching oriented liberal arts colleges for either men or women. These results reveal a gendered component to advisor sponsorship, where it has a positive effect for men with research preferences, but a somewhat mixed effect for women with teaching preferences.
There is also a difference between male and female faculty in how the prestige of their doctoral institution aligns with preferences to impact placement. Results show that even those female faculty who reported a preference for research oriented institutions are more likely to be employed at a liberal arts college if they come from a prestigious doctoral program. Not surprisingly, the effect is slightly stronger for those with a teaching preference.
Notably, and consistent with the full model, results show no gender effects in how individual preferences for a teaching intensive environment affect institutional type placement. Individual accomplishments, in the form of a dissertation award, also function similarly for men and women, in impacting the likelihood of placement in a Research Extensive institution. Taken together, these results collectively indicate a world where doctoral prestige and advisor involvement work through mechanisms that are gendered, supporting placement for female faculty in teaching oriented institutions but not high prestige liberal arts institutions and male faculty in research oriented ones.
One possibility that might explain our results with regard to the impact of advisor involvement is the possibility of endogeneity in terms of advisor support.
lives in science how institutions affect academic careers Manual
While we cannot definitely rule that possibility out, evidence suggests that this is not the case. A t-test reveals no statistically significant difference in terms of advisor sponsorship across preferences. Likewise, if we estimate a regression analysis using all the variables from the full model with advisor sponsorship as a dependent variable, the results show an insignificant coefficient for teaching preference.
There are, however, gender differences, and women report receiving less advisor sponsorship than men, which is consistent with other research that has found advisors being less willing to collaborate with female advisees, for example [ 22 ]. While there may not have been differences in terms of advisor sponsorship across preferences, we do have evidence of differences in terms of advice provided to respondents, as shown in Table 5. Advisors are more likely to suggest research intensive positions, and rarely advise seeking teaching intensive positions, to those with a stated preference for research oriented jobs.
For those interested in teaching positions, however, the advice is evenly split. That is, for those with a stated teaching preference, the advisor is just as likely to recommend a teaching oriented position as they are to recommend a research oriented position.
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The result here is that while there may not be significant differences in terms of reported things letters, calls, etc. Interestingly enough, and unlike our full models, there are very few differences in terms of gender.
Working in physics: A physicist's life-cycle
The only one above to be significant in a t-test is related to advisors suggesting more competitive positions than the respondent was interested in. Women with a teaching preference are more likely to report that their advisor advised them to seek a more competitive position than men with a teaching preference.
As a result, gender differences in terms of actual employment outcomes and preferences seem to be based not on reported levels of advisor sponsorship or advisor reactions to those preferences, but on factors beyond the scope of our study. For example, there may be qualitative differences in terms of advisor sponsorship e.
We cannot discern between these possible causes, though recent research [ 55 ] provides some evidence for the latter hypothesis. The main contribution of our work is that it highlights factors that may result in a career mismatch in the academic marketplace, some of which vary by gender.
As we have noted, not all PhD scientists are interested in intensive academic research careers. A range of personal and professional factors shape academic career preferences. The fit of an individual to their position relates to several positive work-related outcomes, including self-efficacy, job satisfaction, and attraction to the organization and intentions to accept a job offer within the context of the job application process [ 56 — 58 ]. Specifically in the academic workplace, a host of negative consequences has been associated with such mismatches, including reduced income, increased turnover, and reduced job satisfaction [ 59 , 60 ].
The meaningful role that doctoral advisors play in the academic job search of a newly minted PhD is expected. Our results show that doctoral institutional prestige and advisor involvement in the job search process are substantially important in academic careers, but they are important in very different ways.
Advisors play a key role for those wanting to pursue careers at research oriented universities. This seems to be in part because of a strong relationship between advisor involvement and preference i. But even taking this into account, advisor support is still important when we look only at those with a research preference.
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This is also consistent with studies of PhD recipients with interest in non-academic careers, which also note a lack of advisor support [ 1 , 25 ]. Advisor influence seems to disappear when we look at those individuals who would prefer a teaching oriented career, even for those who graduate from the most prestigious teaching institutions. If advisor influence is limited to those who want to pursue a research oriented career, doctoral prestige behaves much more like a form of capital [ 41 ].
When Bourdieu discussed the forms of capital, he used the capital analogy as something that could be deployed to achieve a certain social status. Those who prefer a teaching oriented career are able to transform that prestige into a greater likelihood of teaching at Liberal Arts colleges, where our data have shown that individuals are more likely to report satisfaction with their teaching obligations see Materials and Methods section. And for those with research aspirations, prestige opens doors at the more resource rich Research Extensive institutions.
Besides differentiating between the impact of advisors and institutions, this finding is remarkable because it indicates that previous research has actually underestimated the importance of prestige in the academic labor market. As noted previously, most research on academic prestige has found that within Research Extensive institutions there is a caste [ 12 ] that tends to come from the same elite institutions.
We have shown that those from highly prestigious institutions who have a teaching preference are more likely to work at Liberal Arts colleges. Alumni from elite departments that land at places other than top ranked research institutions may do so by following their preferences. If not for those preferences, we could imagine a much more significant dominance of these elite departments within research oriented universities and colleges. A few caveats are in order. As is the case in most existing research on academic careers, our study suffers from survival bias.
While our sample goes beyond many previous studies by including different institutional types, it is still limited by the fact that we only have data on tenured and tenure track faculty. Research on individuals who move into non-tenure track academic positions e. It may very well be the case that the impacts of prestige and advisor sponsorship are even greater than estimated here if we consider those who involuntarily leave academia.
Our results are hampered by our lack of data on those who exit academia all together, or do not choose it in the first place. Given this, our results are specific to those who persist in the academic workforce. Related, we also lack data on the institutional culture and support mechanisms for career choices in our respondent doctoral institutions. Given this, we are not able to examine the cultural and other factors that matter in early career placement. Another important caveat is that we only have data from one point in time, and the information we have on preferences is based on individual recollection.
To the extent that it is possible, we have tried to address that by confirming our results with different samples. While we presented results from a sample with a full range of career stages, our results are substantively consistent if we focus only on junior faculty or on those who are on their first tenure track appointment. Still, there is always the possibility that people may remember their initial career preferences inaccurately. Thus, some caution should be observed in our interpretation of results.
More comprehensive qualitative studies might be able to shed some light on these issues. To contextualize our research question and subsequent analysis, we first provide a descriptive analysis of the initial career preferences and current placement of our survey respondents. Using frequencies and a comparison of means we examine the extent to which a mismatch of preferences and placement exists. We also use a descriptive model which allows us to control for various demographic and other background factors in explaining mismatch. Next, to test the hypotheses noted above, we use a multinomial logit model[ 61 ] to address how career preferences, institutional prestige and advisor support explain career placement.
Multinomial logit models are among the most popular methods for analyzing issues where discrete choices are at play. By using this method, we can estimate how different variables affect the probability of a given outcome for each observation. This approach is ideal for our purposes, given that our outcomes exist in the form of a nominal variable with four mutually exclusive possibilities i. Our models are weighted by sampling probability, as discussed below. To deal with the issue of research versus teaching career placement preference, we ran three different models. One model included the full sample, and had teaching preference as an independent variable, which was also interacted with the key independent variables.
The other two were restricted by gender, to understand the ways in which different factors affect men and women. We are interested in gender differences given overall disparities in STEM careers, including that women faculty are employed in Research Intensive Institutions at a slightly lower rate than are men [ 35 ].
Lives in Science How Institutions Affect Academic Careers 9780226327617
The primary data collection for this project involved the implementation of an extensive survey of STEM faculty in the United States. Given this, four STEM fields were selected for inclusion: biology, biochemistry high female representation , civil engineering transitioning female representation , and mathematics lower levels of female representation. Another purpose of the project was to understand career variations across the broader academic STEM workforce. The survey and protocol were approved by the Institutional Review Board as part of Human Subjects protection.
The survey addressed a broad set of items relevant to the study of academic careers in STEM. Sections included individual background, job search experiences, early career preferences, relationship with advisor and mentors, positions held and other advancements, research, teaching and professional activities, and other professional experiences.
Because we are interested in career placement issues and career preferences, we are focusing on individuals who reported having an initial preference for academic careers as opposed to industry or government with either a research oriented or teaching oriented focus, for a total of 2, respondents used in our analysis.