MétaCan
Menu
Back to cohort

Tourism Troubles

2024· book-chapter· en· W4400774892 on OpenAlexaff
Sharlene Mollett

Bibliographic record

VenueOxford University Press eBooks · 2024
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsTourismBusinessGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract On the Panamanian Caribbean coast and the Bocas del Toro archipelago land grabbing and domestic service are mutually constituted and embedded in tourism development in Panama. As land insecurities grow, particularly for local Indigenous and Afro-Panamanian peoples, ongoing dispossession is not simply about land but is simultaneously about land, people, and their bodies. In Bocas, land enclosures are infused with imaginaries that take for granted Black female servitude and Black landlessness. Such imaginaries seemingly lock economically “poor” Afro-Panamanian women into particular kinds of work. The chapter entangles feminist political ecological assertions that struggles over nature are embodied struggles with intersectional and relational understandings of land and body. It shows how a logic of elimination operates within the legal geographies of residential tourism development, and in so doing highlights the historical and contemporary ways in which Afro-Panamanian women are naturalized as criadas (maids), a process that accompanies land enclosure. Blending ethnographic and historical data collection, the chapter illuminates how Afro-Panamanian women’s livelihood struggles reflect both their acquiescence to residential tourism development and their resilience in the face of anti-Black patriarchal coloniality in Bocas. It argues that Afro-Panamanian women’s desire for inclusion and belonging in the Bocas del Toro’s tourism enclave—a project that seeks to eliminate Indigenous and Black relations to coastal lands and foster their embodied subjection to foreign nationals—simultaneously reflects their struggles for the right to remain on the coast.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.952
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.174
Teacher spread0.153 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooksSame topicAgriculture, Land Use, Rural DevelopmentFrench-language works237,207