Scientific and technical human capital
Contents
Main
Bozeman and colleagues (2001, 718)[1] more abstract formulation of ‘scientific and technical human capital’ pairs an ‘expanded notion of human capital’ with a ‘productive social capital network´. Or alternatively, ‘the sum of researchers’ professional network ties and their technical skills and resources’ (Bozeman and Corley 2004, 599)[2]. They argue that educational qualifications should not be understood as either an indicator of homogeneous human capital or as an end point in human capital acquisition. Rather both training and experience are heterogeneous, and individual scientific careers are somewhat unique trajectories of ongoing human capital accumulation.
Scientists’ technical human capital is defined by three dimensions:
- Cognitive skills – those cognitive abilities (maths reasoning, memory, ability to synthesize) that are largely independent of context or more likely interact but are not determined by context. Not only ‘scientific’ abilities (2001, 726)[1]
- Substantive scientific and technical knowledge – formation and education, understanding or experimental and research findings (2001, 727)[1]
- Context skills – knowledge accumulated by doing and creating and including tacit knowledge, craft skills, and knowledge specific to the design and implementation of specific research or experimentation plans (2001, 727)[1] not directly applicable but provide heuristics and analogies for other contexts.
The extent to which an individual scientist has particular ‘loadings’ of these factors will shape their career path. Evolution in capacities of these dimensions over time also shapes the possibilities in terms of career trajectories. These dimensions overlap and are in part co-constitutive of each other, but relative weightings determine to some degree the kinds of work roles within teams or other collectives that a scientist is most suited for (cf. habitus, Bourdieu).
However, human capital represents only half the resources available to scientists, the remainder being available through a researchers’ accumulated social capital. Social capital is embodied in the sum of professional and personal interactions and relationships in which an individual is embedded and which increase the resources available to them.
Social capital is defined along two dimensions:
- The institutional setting of the network partner (firm, NGO, Govt institute, etc.)
- Role of the partner (entrepreneur, colleague, funding agency, etc.)
These dimensions combine into the social capital network. In terms of the formal analysis of a social capital network, insights from SNA (Burt, Granovetter) also show that the configuration of extended network roles in terms of centrality, density and brokerage can also affect the resources that are available to an individual. Positioning within networks thus has career implications as well.
The most important parts of the social capital network are the ‘knowledge value collectives’ in which a researcher is involved. Knowledge value collectives (KVCs) are a ‘set of individuals connected by their uses of a body of scientific and technical knowledge’ and are smaller and less durable than scientific disciplines (Bozeman and Rogers 2002, 777)[3]. The basis for choices of research questions or collaborators in the S&T human capital model may thus be somewhat different to that in a model of disciplinary peer communities.
Contributions to measurement concepts
Research collaboration and networking
This concerns social capital & networks.
Inter-sectoral mobility
This is related to the work-experience of individuals.
Sources
- ↑ 1.0 1.1 1.2 1.3 Bozeman, Barry, James S. Dietz, and Monica Gaughan. 2001. “Scientific and Technical Human Capital: An Alternative Model for Research Evaluation.” International Journal of Technology Management 22(7/8):716. Retrieved (http://www.inderscience.com/link.php?id=2988)
- ↑ Bozeman, Barry and Elizabeth Corley. 2004. “Scientists’ Collaboration Strategies: Implications for Scientific and Technical Human Capital.” Research Policy 33(4):599–616. Retrieved November 17, 2014 (http://linkinghub.elsevier.com/retrieve/pii/S0048733304000162).
- ↑ Bozeman, Barry and Juan D. Rogers. 2002. “A Churn Model of Scientific Knowledge Value: Internet Researchers as a Knowledge Value Collective.” Research Policy 31(5):769–94. Retrieved (http://linkinghub.elsevier.com/retrieve/pii/S0048733301001469).
