academic-writing

name	academic-writing
description	Use when drafting sections or editing for clarity. Provides paragraph architecture (topic→evidence→interpretation→bridge), per-section tense discipline, hedging ladders, banned patterns, signal-word banks, and language-specific conventions (Turkish register, English articles). Covers paraphrase discipline with source fidelity.

Academic Writing: Core Conventions

Paragraph Architecture (Universal Model)

Every paragraph should follow: Claim → Evidence → Interpretation → Bridge.

1. Claim (Topic Sentence)

• Function: States the main idea or assertion of the paragraph.
• Form: Usually the first sentence; sometimes the second (after a transition).
• Examples:
  • "Deep learning has revolutionized image classification tasks."
  • "Prior studies disagree on the effect of X."
  • "Method A has three major limitations."

2. Evidence (Supporting Material)

• Function: Grounds the claim with data, citations, or examples.
• Forms:
  • Citation: "Research shows that [@author2024key]."
  • Data: "Our experiments yielded a 92% accuracy rate."
  • Example: "For instance, in the MNIST dataset, convolutional networks outperformed…"
  • Logic: "If we accept that X leads to Y, and we observe X, then…"

3. Interpretation (Explanation)

• Function: Explains why the evidence matters; connects it to the claim.
• Form: "This indicates that…" or "What this suggests is…" or "In other words…"
• Example: "This 5% improvement is significant because it suggests that the proposed loss function better captures…"

4. Bridge (Transition)

• Function: Connects this paragraph to the next; shows flow of thought.
• Forms:
  • Forward-looking: "Having established X, we now turn to Y."
  • Comparative: "Similarly, prior research on Y…"
  • Causal: "Because X holds true, the implications for Y are…"

Full Example

Claim: "Deep learning models trained on insufficient data often overfit, reducing generalization to unseen examples." Evidence: "Chen et al. (2023) found that a CNN trained on only 500 images achieved 87% accuracy on training data but 61% on held-out test data ([@chen2023name])." Interpretation: "This 26-point gap indicates that the model learned noise or dataset-specific patterns rather than generalizable features." Bridge: "To address this, regularization techniques like dropout and data augmentation have become standard practice in the field."

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Per-Section Tense Discipline

Introduction (Present Tense)

• Describe the field, state general knowledge, pose questions.
• Example: "Neural networks have been the dominant approach for image classification." (present perfect = established fact)
• Guideline: Use present tense to speak about the state of the field. Use past tense only for specific prior findings: "Smith et al. (2020) found that…"

Methods (Past Tense)

• Describe what you did (specific to your work).
• Example: "We recruited 50 participants and conducted semi-structured interviews lasting 60 minutes."
• Guideline: Everything you did is in the past (even if writing in present session). The procedure is complete before writing.

Results (Past Tense)

• Report what you found.
• Example: "Results showed that the proposed method achieved 94.2% accuracy, compared to 87% for the baseline."
• Exception: If presenting data in a table, the table itself is timeless (present tense OK for table headers: "Accuracy (%)").

Discussion (Present Tense + Hedging)

• Interpret findings, compare to literature, theorize.
• Example: "These findings suggest that the loss function improves generalization (present), as evidenced by our results (past). Prior work indicates similar patterns [@citation2024]."
• Guideline: Hedging is appropriate here (you're interpreting, not stating absolute truth).

Conclusion (Present Tense)

• Summarize and look forward.
• Example: "This work demonstrates that X is possible. Future research should investigate whether Y applies to…"

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Hedging Ladder (Claim Strength vs. Evidence Strength)

Match hedging language to your evidence strength:

Strength	Verb/Phrase	Example
5 (Certain)	demonstrate, show, prove, establish	"Results demonstrate that X causes Y." (use only with strong evidence: RCT, multiple studies)
4 (Strong)	indicate, suggest, provide evidence that	"Findings indicate that X likely causes Y." (good evidence: consistent pattern, multiple datasets)
3 (Moderate)	suggest, imply, hint at, appear to	"Results suggest that X may influence Y." (decent evidence: one solid study, needs replication)
2 (Weak)	may suggest, might, could	"These findings may suggest that X could influence Y." (limited evidence: single study, small N)
1 (Uncertain)	may possibly, might tend to	"One might speculate that X possibly influences Y." (very limited, avoid in academic writing)

Examples

Claim	Strength	Hedged Phrasing
Your hypothesis is supported	4–5	"Results demonstrate the hypothesis" (RCT, large sample, clear effect)
You found a pattern but it's not universal	3–4	"This suggests a pattern; further work is needed to confirm"
One prior study found something	2–3	"One study indicates that X; however, replication is needed"
You're speculating	1–2	Avoid or use: "Future work could explore whether…"

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Banned Patterns (Eliminate These)

1. Vague "This" (without noun anchor)

Bad	Good
"The model was trained for 100 epochs. This improved accuracy."	"The model was trained for 100 epochs. This training regime improved accuracy." Or: "As a result, accuracy improved."
"We used data augmentation. This is important."	"We used data augmentation. This technique is important because…"

Fix: Replace "This" with "This [noun]" or rewrite to avoid ambiguity.

2. Chained Nominalizations (noun → noun → noun pileup)

Bad (Hard to parse)	Good (Clear structure)
"The implementation of the adoption of the framework requires understanding of the theory underlying…"	"To implement the framework, researchers must understand the underlying theory…"
"Improvement in model accuracy through regularization application shows regularization method effectiveness."	"Regularization improves model accuracy, demonstrating regularization's effectiveness."

Fix: Use verbs instead of nouns where possible. "Implementation requires" not "Implementation of X requires."

3. Empty Intensifiers (add no meaning)

Bad	Good
"This is a very important finding."	"This finding is significant because [explain why]."
"The results are quite remarkable."	"The results show [specific outcome that is remarkable]."
"The method is extremely novel."	"The method differs from prior work by [specific difference]."

Fix: Show the importance via specificity, not adjectives. Let data/analysis speak.

4. Weak Passivity (hiding the agent)

Bad	Good
"It was found that X improves Y."	"Our experiments show that X improves Y."
"It is believed that…"	"Researchers believe that…" or "Current theory suggests that…"
"The model was trained." (by whom? when?)	"We trained the model for 100 epochs using SGD with learning rate 0.001."

Fix: Use active voice when possible. Passive is OK for methods if agent is clear from context.

5. Hedging Gone Wrong (too much or too little)

Bad (Over-hedged)	Bad (Overconfident)	Good
"It might possibly be suggested that perhaps X could conceivably influence Y."	"X definitely causes Y." (without evidence)	"Evidence suggests that X influences Y."
"One could speculate that…" (avoid)	"Our single experiment proves X."	"Our results indicate X; further validation is needed."

Fix: Match hedging to evidence. Use the ladder above.

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Signal-Word Bank (Transitions & Connectivity)

Contrast / Opposition

• "However," "In contrast," "Conversely," "Yet," "Although," "Despite this," "On the other hand."
• Example: "Traditional methods are faster; however, they sacrifice accuracy."

Concession (accepting a point before arguing yours)

• "Granted," "Admittedly," "One could argue that," "To be fair," "It is true that…"
• Example: "Granted, prior work has shown X; our results suggest Y is also important."

Causality / Reason

• "Because," "Since," "As a result," "Therefore," "Consequently," "Thus," "This explains why."
• Example: "Because the dataset was imbalanced, we used stratified sampling."

Addition / Reinforcement

• "Furthermore," "Moreover," "In addition," "Also," "Similarly," "Likewise."
• Example: "The method is accurate. Moreover, it is computationally efficient."

Emphasis / Importance

• "Notably," "Significantly," "Importantly," "It is worth noting that," "Crucially."
• Example: "Notably, this is the first study to combine X and Y."

Temporal / Sequential

• "First," "Subsequently," "Meanwhile," "Finally," "Earlier," "Following this."
• Example: "First, we collected data. Subsequently, we analyzed it."

Summary / Conclusion

• "In summary," "In conclusion," "To summarize," "Overall," "In short," "To recap."
• Example: "In summary, our findings suggest three key implications."

Example / Illustration

• "For instance," "For example," "Specifically," "To illustrate," "Consider…"
• Example: "Our method applies to various domains. For instance, in medical imaging, it achieved 98% accuracy."

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Paragraph Cohesion Checklist

Before submitting a draft:

• Does every paragraph have a clear topic sentence (claim)?
• Is there evidence (citation or data) supporting the claim?
• Is there interpretation (why does this matter)?
• Does the paragraph end with a bridge to the next paragraph (or final sentence connects to next idea)?
• Do sentences within the paragraph use signal words (however, moreover, for instance) to show relationships?
• Is tense consistent and appropriate for the section?
• Are hedges matched to evidence (strong claim = strong evidence)?

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Language-Specific Guidance

Turkish Academic Writing

See turkish-academic.md for:

• Passive voice norm (yapılmıştır, bulunmuştur)
• Term unity (one concept = one Turkish term throughout)
• TDK number/unit conventions
• Common expression errors

English Academic Writing

See english-academic.md for:

• Article usage (the #1 error of Turkish authors)
• Collocation bank for academic verbs
• Nominalization-overload repair patterns

Paraphrase Discipline

See paraphrase.md for:

• Source-faithful paraphrase technique
• "Change the structure too" rule
• Self-check questions
• When to quote verbatim (with page-number discipline)

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Claim Strength: Never Say More Than Your Source

A citation can be real, resolvable and correctly formatted while the sentence built on it still misrepresents the cited work. /verify-citations answers "does this reference exist?"; it cannot answer "does it say that?".

The ordered scale (rungs 0–5, TR + EN), the one-directional rule (writing weaker than your source is always safe; writing stronger is the defect), the attributive-participle trap ("reduced capacity" is an outcome, not a claim), and the evidence→rung table live in claim-strength.md.

Deterministic half: python scripts/claim_check.py compares each cited sentence's rung against the evidence cards for the sources it cites, and flags empirical assertions carrying neither a citation nor an own-work marker. WARN-only — a rung difference is often legitimate; the check exists so you make that call deliberately.

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Quick Reference: Tense Table

Section	Tense	Example
Introduction	Present (general knowledge); past (prior studies)	"Research shows that X is important. Smith et al. found that…"
Methods	Past (what we did)	"We recruited 50 participants. Data were analyzed using…"
Results	Past (what we found)	"Results showed a 5% improvement. The method achieved 92% accuracy."
Discussion	Present (interpretation, theory); past (our results)	"Our findings suggest that…. We found that…"
Conclusion	Present (broader implications, general statements)	"This work demonstrates that X is possible. Future work should investigate Y."

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One-Sentence Summaries Per Reference File

• turkish-academic.md: Use passive voice as the norm, maintain term unity (EN term in parentheses on first mention), apply TDK conventions for numbers/units.
• english-academic.md: Master article usage (a/an vs. the), use strong academic collocations (not "have an issue" but "face a challenge"), avoid nominalization overload.
• paraphrase.md: Paraphrase with structure change, cite the source, check that meaning is preserved without copying phrasing, quote verbatim only for key passages (with page numbers).
• claim-strength.md: Keep every claim on the rung its source actually supports; weakening is safe, strengthening is the defect; watch for adjectives silently promoted into verbs.

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Practice Exercises

Exercise 1: Fix the vague "this"

"The model achieved 95% accuracy. This was a major breakthrough."

Answer: "The model achieved 95% accuracy. This performance was a major breakthrough (an 8-point improvement over prior work)."

Exercise 2: Fix the nominalizations

"The implementation of the algorithm through the use of data augmentation resulted in accuracy improvement."

Answer: "Implementing the algorithm with data augmentation improved accuracy."

Exercise 3: Match hedging to evidence

Evidence: One study with n=20 found X. Your phrasing: "X is proven."

Answer: "Preliminary evidence suggests that X may occur; larger studies are needed to confirm."

Exercise 4: Add signal words

"The method is fast. It is accurate. It is cheap. These are advantages."

Answer: "The method is fast. Moreover, it is accurate. Furthermore, it is cheap. Together, these characteristics make it attractive for deployment."

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References & Resources

• See reference files for language-specific guidance:
  • reference/turkish-academic.md
  • reference/english-academic.md
  • reference/paraphrase.md
  • reference/claim-strength.md
• APA 7 Style Guide: aspastyle.apa.org
• Merriam-Webster for academic collocations and usage.