New Types of Careers in the Knowledge Economy ? Networks and boundaryless jobs as a career strategy in the ICT and multimedia sector
Bibliographic record
Abstract
Over the last few decades, many countries have found themselves in a context characterized by the spread of the knowledge-based economy (OECD, 1996; Foray and Lundvall, 1995; Soete, 1996; Storper, 1995). The Knowledge Economy implies a farreaching transformation of the labour market, particularly in terms of job mobility and career development (Christensen, 1989). In this context, careers are increasingly fragmented, and people are more mobile in the labour market, with social networks playing an important role in this job mobility as well as in professional development. Although not everyone is concerned by these developments, and there are some resistances to this change in work organization and careers, it is clear that some sectors, particularly the New Economy creative sectors (multimedia, New media such as digital video, tv and the like, ITC), are very much concerned by these developments. This constitutes a considerable challenge for occupational development, since it used to be provided by the firm within internal labour markets and this can no longer be the case when people are more mobile. Now, especially in sectors such as ICT (Information and Communication Technologies) and multimedia, characterized by extreme mobility between firms, but also by a need for permanent professional development, the challenge for firms to capture strategic advantages presents itself in a new perspective. In our view, these new careers, described by some as "nomadic" (Cadin, 1998; Arthur, Claman and De Fillippi, 1995; De Fillippi and Arthur, 1998; Hendry and Jenkins, 1997; Hendry, Arthur and Jones, 1995) and by others as "discontinuous" (Tremblay, 1997), lead us to question our vision of organizations and organization theory. Let us add that in terms of Communications and Strategies, the sector and the questions it poses are surely important, since they call into question the impact of the Communications sector and its developments in multimedia and ICT, as well as management strategies that may be developing in these sectors. Over the last two years, we have conducted research on people who work in the ICT and multimedia industry. Our paper will dwell on the new types of careers developing in these sectors, highlighting a new form of work organization, which is more informal and rests very much on social networks developed by the workers in these sectors. We will highlight the new type of careers and work organization that is observed and conclude with some questions which need to be addressed in the context of the development of ICT and multimedia and particularly as concerns careers and work organization of the future. The new economic sectors characterized by mobility and nomadic behaviour present insights that can be useful in modernizing Work Organization and Career theories, although it may be too soon to draw conclusions as to what this new theoretical vision should be. Clearly, the new vision would need to take into account new forms of learning, new forms of careers offered by firms, aspirations of young workers in these sectors, etc. It also should take into account the specificities of networks of workers in the ICT and multimedia sectors, as well as the construction of careers of professionals and technicians who are at the core of the competitive advantage of the ICT and multimedia firms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".