Bibliographic record
Abstract
France's Lost Empires brings together ten essays that collectively investigate the historical, cultural, and political legacies of French colonialism and, specifically, the endings of the French empire(s). Combining analyses of three "lost" territories (Canada, India, and Saint Dominigue) of the "first" French colonial empire, that of the Ancien Regime, with investigations of the decolonization of the "new" colonies of the "second" French overseas empire (specifically in North Africa), the essays presented here investigate the ways in whicih colonial loss has been absorbed and narrativized within French culture and society, and how nostalgia for that past has played a fundamental role in shaping French colonial discourses and memories. Beginning with the Haitian Revolution and its historicization during the 1820s and ending with an examination of the "postcolonial" republic at the end of the twentieth century, the chronological structure of the volume serves to reveal the extent to which the memories of territorial loss have been sustained throughout French colonial history and remain evident in current metropolitan representations and memories of empire. In analyzing the longevity of these tropes of loss and nostalgia, and their importance in shaping France's identity as a colonial power both during and after periods of colonization, France's Lost Empires reveals a basic premise: it is not simply successful conquest which creates a self-validating colonial discourse; failure can do so too. Indeed, the pervasive and tenacious nostalgia for past colonial glories, variously identified by the contributors to this volume, suggests that, for some, the emotional attachment to France's colonies has not waned and remians today as it was in nineteenth-century France.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".