Bibliographic record
Abstract
Abstract From the earliest days of Spanish and Portuguese colonial rule up until the late 19th century, banana cultivation in the Americas was carried out mostly by smallholders. That changed around 1880, when schooner captains based in Boston and New Orleans began to buy bananas in the Caribbean and sell them in the United States. In the geographically small countries of Central America, a couple of US-based banana companies have wielded enormous influence. The United Fruit Company (now known as Chiquita) acquired so much power in Guatemala and Honduras that it came to function as a state within a state, giving rise to the notion of “banana republics.” The company consolidated its power through various means: it installed authoritarian civilian and military governments that gave concessions to land, railroads, and ports; it divided its labor force along ethnic and racial lines; it built hospitals, schools, workers’ barracks, and houses for its management; and it used massive amounts of pesticides and herbicides in a capital intensive effort to cultivate varieties of the fruit that North American consumers came to expect but which were susceptible to Panama disease and Black Sigatoka. Bananas and plantains are a dietary staple throughout the tropics, and the diseases that beset the Gros Michel and Cavendish varieties that are grown on monocrop plantations threaten a vital source of healthy and relatively cheap calories that much of the world has come to rely upon. In recent years, consumers and civil society groups have organized to demand more socially and environmentally responsible bananas, creating organic and “fair trade” alternatives to conventional “free trade” bananas.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".