Bibliographic record
Abstract
Autonomous Communities Seventeen autonomous communities or regions [Figure 1], were formed by the 1978 Spanish constitution, which defines as a parliamentary monarchy. Background to Developing this Article One year before the September 11, 2001, terrorist attacks against the United States I visited Spain. I started out in Madrid, then visited Seville, Toledo, and Algeciras, crossed the Straits of Gibralter to visit Morocco for several days and returned to Spain, visiting Malaga and the gold coast, Barcelona, and the Balearic island of Mallorca. I also visited two northern coastal cities in the Basque Region: Bilbao and San Sebastian. In preparing for the trip, I gathered information about business and industry in from Greg Simon, at the Spanish Embassy in Washington, D. C. I learned about Spain's economy, labor force, and career services from a wide range of books and journals, and from the CIA World Factbook. Through my membership in the International Association of Career Management Professionals, in advance of the trip to I contacted Jose Arno Esteve, Director of the outplacement consulting firm Analisi-Nic in Barcelona, who in turn introduced me to two Madrid career management consultants: Juan Carlos Cubeiro, then of HayGroup, and Pedro Navarro, President of Andersen Consulting-Spain; and also to Professor Jose Ramon Pin Arboledas, of the IESE Business School, Universidad de Navarra [Madrid and Barcelona]. Professor Pin presented me with his monograph on the career path of the Spanish MBA graduate. Both Sefior Cubeiro and Sefior Navarro presented me with copies of the books that they wrote about career transition in Spain. I met for several hours with Sefiors Cubeiro, Navarro, and Pin, and learned from them about private profit-making support services and outplacement services for career management in Spain. When I reached Barcelona, I had a full discussion of career transitions in with Jose Arno. He also introduced me to Anselm Divi Torino, Director of Human Resources, SanofiAventis in Barcelona. Each of these discussions with experts was insightful, and are highlighted below. From a suggestion by Dick Knowdell, the publisher of this Journal, I consulted with Professor Norman Gysbers of the University of Missouri-Columbia, who is a prominent U. S. representative to the International Association for Vocational and Educational Guidance. He provided an introduction to Senora Elvira Repetto Talavera, of the Universidad Nacional de Educacion a Distancia. Sefiora Repetto is on the board of directors of the International Association for Educational and Vocational Guidance [IAEVG]. She made available to me her country paper presented at the lAEVG-associated International Symposium in 1999 and later when I met her again at the IAEVG International Symposium in Vancouver, Canada, she provided her 2001 country paper. Sefiora Repetto also facilitated introductions to a number of international career guidance experts attending the IAEVG International Symposium when we met in Vancouver. Sefiora Repetto also very thoughtfully introduced me to Seflor Javier Romeo, who also gave me a personal interview in Madrid. Senor Romeo is Director, National Institute of Employment, Madrid, Spain, and Director, Project EURES in Brussels, Belgium. This combination of research and the interviews with academic, government, private industry and consulting experts in were the sources for this article. Background: is Different Espana es diferente tells us that Spain is different. To know the Spanish economy and current history is to understand better the origin and evolution of its career services. The estimate of Spain's population for 2005 is 40,341,462 persons. Some 77 per cent of the population lives in towns and cities. Spain's labor force consisted in 2003 of 18.2 million persons. Of these, 6 per cent were employed in agriculture, forestry, and fishing; 32 per cent in manufacturing, mining, and construction; and 62 per cent in services. …
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".