Bibliographic record
Abstract
Human geography is torn between two tendencies : the ecological tendency examines man in interrelation with the natural environment, the chorological tendency places the accent on the changes which man bas produced in the landscape. Man, in this sense, is a genuine geographic factor. There are two extreme positions : one tends to point out the role of determinismof the natural environment, the other seeks « the key to geographical explanation » in the culture of man. By means of examples taken in part from his own research, the author, while according an essential place to culture in geographical interpretation, draws attention to the fact that culture itself is explained in large part by its genetic environment. For example, one could not imagine the peasant cultures of l'Asie verteand the ideal of nomad and urban life of l'Asie fauve —marked by the imprint of Islam —being interchanged, the one for the other. The expansion of peoples of western civilization, first of all, and then the ubiquity of industrial civilization, appear to contradict an ecological conception of the relation between man and environment. But the industrial revolution it self was favored by a combination of conditions that man was able to exploit and that explains the rise of western and central Europe, just as the lack of the conditions explains the technological immobility of the Mediterranean. Research into ecological correlations is not the essence of human geography. Human geography ought to remain « the description and interpretation »of the human elements of the landscape, of regions, and of continents. Its fundamental method remains observation. Spiritual factor s, biological factors, superior forms of economic life, and social structures are not of interest to human geography except in so far as they are evident in the physiognomy of areas. The interpretation, with delicate gradations as in all the social sciences, ought to be based simultaneously on the « influences of the environment »and on the resources of the culture of a given people. It thereby reflects both determinism and the freedom of choice in all human 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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.006 | 0.055 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".