Inter‐corporate ownership and diversification in the Canadian economy 1976‐1995
Bibliographic record
Abstract
Purpose To test the hypothesis of increased specialisation during the 1980s in the aggregate pattern of intercorporate ownership in the Canadian economy. Design/methodology/approach The network of ownership between enterprises and subsidiaries is characterised for the period 1976‐1995 using data for the population of medium‐sized and large Canadian corporations collected by Statistics Canada. Findings Aggregate diversification declined slightly over the period in terms of the average number of industry groups in which enterprises have subsidiaries. However, there was an increased likelihood that subsidiaries were outside of the core industry group of the enterprise. Research limitations/implications The data provide insight into ownership changes across the economy and are not sensitive to changes in a few very large firms. However, a weakness of these data is that the ownership linkages are not weighted to reflect the economic importance of the enterprises involved. There is evidence that the pattern of inter‐corporate ownership is different between manufacturing and service sectors. Future research should treat these separately. Practical implications Increased specialisation to the core industry of an enterprise has implications for the management skills required to design and manage networks of independent firms (for example, through strategic alliances), the performance expectations and risks taken by shareholders, and the commercial and tax policies set by government. At an aggregate level, a reduction in diversification may change the industrial structure of the economy, with sectors less integrated through ownership relationships, and thus potentially more sensitive to patterns of market exchange. Originality/value Much of the literature on the effect of ownership restructuring on aggregate diversification is focused on the US economy, and there is little empirical evidence in the Canadian context. The data are unique, representing a population of medium‐sized and larger firms. To our knowledge there are no published analyses of the ownership structure represented in these data.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".