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Record W2124740781 · doi:10.1145/986710.986720

The programmer life-cycle

2004· article· en· W2124740781 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACM SIGSOFT Software Engineering Notes · 2004
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsProgrammerProductivityComputer scienceConstruct (python library)SoftwareProgramming languageEconomicsMacroeconomics

Abstract

fetched live from OpenAlex

The traditional analysis of programmer productivity ignores the reality that work rates of programmers are variable over time. Not unlike the software systems they construct, programmers follow a predictable life-cycle. However, the programmer life-cycle is not comprised of activities but rather by phases that directly affect and predict productivity. The sequence of phases is: euphoric, productive, irreplaceable, resentful, bored, and unproductive. Overall productivity is characterized by an initial six month period of intense interest, at which time productivity rates are often an order of magnitude higher than the oft-quoted 500 LOC/month average. After a short period of volatility, the programmer then enters a prolonged phase of steadily dwindling interest, resulting in productivity rates that mimic the average. Each time a programmer switches employers or begins a significantly new project, the life-cycle starts anew.

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.

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)0.337
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.600
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.337
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.015
GPT teacher head0.246
Teacher spread0.231 · 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