Educating the global workforce : knowledge, knowledge work and knowledge workers
Bibliographic record
Abstract
Introduction SECTION ONE: WHAT COUNTS AS WORKING KNOWLEDGE AND WHO SAYS SO. Knowledge in the knowledge economy (To be invited: Robert Reich, US) Indigenous perspectives on knowledge and knowing at work, (TBC) Zane Ma Rhea (Australia) and Makere Stewart Hawawira (New Zealand)), Alternative perceptions of the idea of skill Traditional concepts of vocational knowledge and skill, Nancy Jackson (Canada) Cross cultural critique of potentially normalising international training programs like the Harvard-style MBA Rui Yang (China) Intersections of working knowledge and community knowledge-building, Mary Hamilton's (UK) SECTION TWO: KNOWING AND WORKING IN THE GLOBAL ECONOMY Political economy (TBA Peter Sawchuk, Canada) Work-learning trends in Europe Knud Illeris' (Denmark) Eastern European attempts to reframe their vocational training system for the global economy (Turkey -- TBC). The impact of ICT on working knowledge: Bernard Holkner's (Australia) chapter focuses on the technical constraints and possibilities of technologically hybrid workspaces from a socio-technical perspective. Richard Edwards and Kathy Nicoll (Scotland) bring an Actor Network Theory perspective to technologically enabled work, Shauna Butterwick (Canada) brings a gender perspective to such workplaces Indrajit Banerjee (Singapore) a Pacific Rim perspective Organizational knowledge building (eg 'Learning Organizations' and 'Organizational Universities) from critical managements studies perspectives: Harry Scarborough's (UK) and Sharon Howell, Vicki Carter and Fred Scheid (USA). SECTION THREE: WORK, WORKING LIFE AND WORKING IDENTITIES Case studies:the global economy and work-related education in local communities *South Africa, Catherine Kell *Mexico, Susan Street *India, Anita Rampal The formation of pedagogic identities from different perspectives: Australia, Stephen Billett (TBC), Canada, Miriam Zukas (TBC), Life history and the trajectory of the individual worker, Phil Hodkinson's (UK) and Henning Salling Olsen's (Denmark) Discursive production of working identities through workplace education centred on literate practice, Clive Chappell, et al(UK and AUST) The role of mentoring in producing and reproducing certain kinds of working knowledge and working identities. Anita Devos (AUS) SECTION FOUR: CHALLENGES FOR WORK-RELATED EDUCATION. School to work transition in Europe, including the new European States (Keith Forrester, UK) The impact of the global economy on mass schooling in emerging economies ( Ram Giri, Nepal) Education and the contingent workforce from a critical race/feminist perspective (Kiran Mirchandani, Canada) Two chapters on the new challenges to trade union training/labor learning, one from an international perspective (eg Alan Brown/John Payne Uk, Jeff Taylor Canada). Specific challenges: case studies from South America and Africa (TBA) Gender and trades (TBC, Bonnie Watt Malcolm and Alison Taylor, Canada) Tension between the global/local in work-related education (Appaudurai (India/US), Alternative Fazal Rizvi (Australia/USA) . Conclusion
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".