High Tech Atlanta: Global Links Deep in Dixie/ Atlanta et la Haute Technologie : Des Liens Globaux Bien Ancres Dans le Dixie
Bibliographic record
Abstract
High technology companies in Atlanta provide a major job growth engine in this premier business centre of Georgia and the Southeast. Data rankings indicate the metropolitan area's relative strengths, augmented by interviews discussing the crucial human network synergies that created and sustain Atlanta's computer software and telecommunications sectors. A feature of the region's technology employment base is its Asian face, primarily from India and China. This research discusses the origin, extent, and composition of high technology clusters in metropolitan Atlanta's four core counties. Les entreprises des technologies de pointes d'Atlanta representent un moteur de creation d'emplois important dans le milieu des affaires industrielles et commerciales de Georgie et du sud est. Les donnees indiquent la force relative de la metropole, et les entrevues que nous avons menees mettent au premier plan la synergie cruciale du reseau humain qui a cree et soutenu les secteurs primordiaux d'Atlanta en genie informatique et en communication. Une autre dimension de la base d'emplois en technologie de la region est celle de l'Asie, essentiellement de l'Inde et de la Chine. Cette recherche discute de l'origine, de l'etendue et de la composition des grappes de haute technologie dans quatre comtes au coeur d'Atlanta. Introduction Cities seek to be known as high technology job magnets due to the economic benefits accruing to that perception, though only limited understanding and no agreement exists as to either the basis for the high technology label or the types of jobs encompassed. Attaining this favourable designation is particularly important for urban areas in the southern United States, historically perceived as a lagging region. The following research examines how metropolitan Atlanta developed as a mecca for high technology activity, in what sectors its locational strength lies, and where within the metropolitan region related businesses and employees cluster. The city's prominence in this critical sector rests largely on a strategically timed confluence of embedded attitudes prioritizing economic success and the presence of entrepreneurial individuals in business, politics, and educational institutions. Atlanta is widely viewed as the economic centre of the southern United States. As enunciated by former Mayor Hartsfield, who directed and presided over the major boom phase of Atlanta's growth, Dixie's leading metropolis is busy to hate [non-whites] because it is too occupied with making money. A demographic focus of this research explores the prevalence of Asians, especially Indians and Chinese, in the high technology/professional specialty occupational category. The face of 21st century Atlanta increasingly assumes a more global and higher technology profile than apparent in its previous public image. The following section lays out the theoretical framework for explaining the success of Atlanta as an urban high technology magnet within a developmentally challenged region (Kantor 1995). A detailed case study of the southeast's leading metropolis traces the beginnings of high technology stemming from the presence of the Georgia Institute of Technology and the meeting of several entrepreneurial business and political leaders. The examination culminates by assessing Atlanta's current position within American high tech locations, and its new global labour presence. Predicting Prominence The highly agglomerated nature of Atlanta's technology sector fits within several related theoretical frameworks. Their particular applicability to the Atlanta case study is noted as each one is discussed. A complementary set of theories addresses how a national level metropolitan economy emerges from a lagging region. Agglomeration economies enhance groups of closely located companies by drawing on similar embedded strengths. This demonstrably increases both the visibility and reality of those strengths in the locality and their resident related companies. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".