Comparing and Contrasting International Business and Economic Geography Perspectives on the 'Space, Place and Organisation' of Service Offshoring
Bibliographic record
Abstract
This paper adds to the growing body of work at the interface of International Business and Economic Geography by comparing and contrasting the perspectives of these two disciplines on geographic and organisational aspects of ‘service offshoring’. The intention is to work towards an enhanced, inter-disciplinary understanding of this important phenomenon; this paper takes some initial steps. The paper begins with an initial comparison of the scope and key concerns of the two disciplines and a brief review of some recent studies of service offshoring from both fields. The main section of the paper comprises a comparative discussion, organised around four focal themes relating to the conceptualisation of ‘place, space and organisation’ in the specific case of service offshoring: (1) Conceptualising ‘organisation’: theorising the firm, extended network contexts and intra-firm network relations; (2) The geographical unit of analysis and issues of spatial scale; (3) Conceptualising location and the firm-location ‘nexus’; (4) Conceptualising ‘distance’ and its influence on firm behaviour.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.005 | 0.035 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".