Entering and practicing within the construction industry in China: a guide for contractors
Bibliographic record
Abstract
After Canada, China is the largest country in the world by land mass and is the most populated country in the world with of over 1.27 billion people (Encarta Encyclopedia, 1996). Until 1978, China was largely isolated from the Western world largely due to its social and economic policy of the Mao Zedong era. However since the ‘Open Door Policy’, which saw parts of China, opened up to international trade, investment, the rate of modernization has been nothing short of phenomenal. China is now set to be world’s next Economic Superpower. At the cornerstone of China’s economic reform and modernisation policies has been to attract foreign technology, expertise and investment particularly through joint venture and other arrangements. The main focus on the upgrading of basic industries, particularly construction (www.moftec.gov.cn, 01/10/01). This thesis aims to help foreign contributors to China’s continuing economic development to gain a basic knowledge of these matters by presenting a broad picture of the construction industry in China, by addressing some questions and by attempting to provide some answers. Some of these questions include; • What are the problems? • What are the key design issues? • How is construction organised? • What is the legal framework? • What entry mode should be used? • What type of construction contract should be used? • What type of project delivery system should be used? • What type of procurement strategy should be used? The sheer size and huge population of China lead inevitably to a diversity approach. As a result, conditions, which foreign parties will encounter, can only be indicated, not specified. This thesis intends to give something of the texture of the country, the processes and the environment within which construction takes place. This thesis is intended to be read by a wide range of readers including investors, consultants, financiers, manufacturers, contractors, suppliers and government departments, the detailed needs of each may be lacking. What this thesis does provide is a framework from which future knowledge can be developed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.010 |
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".