Institutions, organizations & identity : building legitimacy in the Arab Gulf
Bibliographic record
Abstract
Invariably, every market has a set of institutions that regulate and define economic activities. Emerging economies may be developing in a way that integrates and blends traditional practices and beliefs with international conventions and standards. In these economies, like in all others, competing logics co-exist and are used to rationalize the persistence of traditional practices and the institutionalization of reforms. The remarkable characteristic of these markets, specifically due to the increasingly globalizing business, is that they often harbour completely diverging institutional logics, including those integral to Western firms' modus operandi and those of local firms building on traditional practices. A neo-institutional theory based theoretical framework is developed to explore the interaction between society, exerting conforming pressures, and organizations, responding to these pressures. In order to explore the applicability of the developed model, a qualitative field study was conducted. Data was collected by interviewing high ranking officers of Canadian and indigenous firms operating in UAE. Among the research findings, organizational identity was found to moderate firms' strategic choices in response to institutional demands. 'Wasta', a unique local institutional artefact, was found to provide firms leverage in manipulating institutional demands
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".