MétaCan
Menu
Back to cohort

In Response to “In Praise of Makeshift Finishing”: On Makeshifting, Publishing, and Storytelling

2025· article· en· W4408157940 on OpenAlexvenueno aff
Jesse Jonkman

Bibliographic record

VenueAnthropologica · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicFolklore, Mythology, and Literature Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPraiseStorytellingPublishingArtLiteratureNarrative

Abstract

fetched live from OpenAlex

Livelihoodsknow how thorough a storyteller he is.Chock-full of vivid scenes of the Choc goldfields in Colombia, the book reads like a subtle proposition in favour of the thrills and rewards of slow writing.It was the cumulative result, as Tubb recounts here, of his choice to spend the past few years revising his doctoral dissertation into a monograph, rather than committing himself to building a portfolio of publish-or-perish articles.Yet it is not an argument of slowness that Tubb is advancing in his petition for "makeshift finishing."In many ways, he is telling us the exact opposite: Do not overthink it; do not spend too much time perfecting the text; get the "something good enough" out there and have it interact with the world.His appeal to makeshifting is a call to align our publishing strategies with "a shorter, more imperfect, contingent, and temporary way of writing"; one in which our publications are not the end result of settled theories and steadfast strategizing, but unstable pieces that are formative of, and formed by, ideas that are always fluid and incomplete.Tubb's thought-provoking piece is categorically anthropological.Stop overplanning the big picture!Put your skill and industry in lockstep with the messy temporalities of ethnographic (and human) practice!To be sure, in his adoption of the makeshift, and attendant rejection of formulae, one hears echoes of previous anthropological critiques of formulistic planning-say, Ingold's (2020, 14) ruminations on "amateur rigour," or Scott's (1998) juxtaposition of state formation with mtis.Tubb's argument also brings to mind

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.298
Teacher spread0.270 · 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
GenreEmpirical

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAnthropologicaSame topicFolklore, Mythology, and Literature StudiesFrench-language works237,207